DETAILED ACTION
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1):
Claim(s) 2 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of Jansen et al. (US 2021/0196219 A1):
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of YOO et al. (US 2016/0300370 A1):
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of XIE et al. (US 2020/0342592 A1):
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Response to Amendment
The amendment was received 7/16/2026. Claims cancel: 13,15,16,17. Claims pending:
1,2,3,4,5,6,7,8,9,10,11,12 and 14,18,19,20,21,22,23,24:
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Claim Objections
Claim 22 objected to because of the following informalities:
Claim 22, last line’s “the preliminary parametric image” is missing “PET” and is interpreted as “the preliminary PET parametric image” consistent with claim 14’s “a preliminary PET parametric image”:
Appropriate correction is required:
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14. (Currently Amended) A system for quality evaluations of parametric imaging in positron emission tomography (PET), comprising:
at least one storage device including a set of instructions; and
at least one processor in communication with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including:
obtaining multiple PET images collected via a PET scan of a target subject, the PET images being dynamic PET images for difference time periods during the PET scan and used to generate a target PET parametric image of the target subject;
for each physical point of the target subject,
determining a pharmacokinetic model corresponding to the physical point, and
determining a PET parametric value of the physical point based on pixel values corresponding to the physical point in the PET images using the pharmacokinetic model of the physical point;
generating a preliminary PET parametric image based on the PET parametric value of each physical point of the target subject;
performing a quality evaluation on the preliminary PET parametric image by:
for each physical point of the target subject,
determining a matching degree of the pharmacokinetic model with respect to the physical point based on the PET images, and
generating a determination result indicating whether the corresponding pixel of the physical point in the preliminary PET parametric image needs to be corrected based on the matching degree; and
in response to determining that a count of physical points whose corresponding pixels need to be corrected is greater than a count threshold,
determining that pharmacokinetic model correction needs to be performed,
correcting the preliminary PET parametric image, and
generating the target PET parametric image of the target subject based on
21. (New) The system of claim 14, wherein the determining a matching degree of the pharmacokinetic model with respect to the physical point based on the PET images comprises:
determining a first time-activity curve (TAC) of the physical point based on the pixel values corresponding to the physical point in the PET images;
determining a second TAC of the physical point based on the pixel values corresponding to the physical point in the PET images and the pharmacokinetic model corresponding to the physical point; and
determining the matching degree based on a similarity between the first TAC and the second TAC.
22. (New) The system of claim 21, wherein the correcting the preliminary PET parametric image includes:
determining target physical points of the target subject whose determination result indicates that the corresponding pixel needs to be corrected;
for each target physical point, determining a new pharmacokinetic model corresponding to the target physical point, and determining a new PET parametric value of the target physical point based on the pixel values corresponding to the target physical point in the PET images using the new pharmacokinetic model; and
correcting the preliminary PET parametric image by updating the PET parametric values of the target physical points in the preliminary PET parametric image with their new PET parametric values.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 120, 121, 365(c), or 386(c) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. CHINA 202310620627.6 05/29/2023, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application.
The claimed:
“histoimage” (claim 10)
is not in Application No. CHINA 202310620627.6 05/29/2023.
Accordingly, claims 10 are not entitled to the benefit of the prior application.
Response to Arguments
I. Determination regarding the benefit of the Priority Application
Applicant's arguments filed 7/16/2026 have been fully considered but they are not persuasive:.
Applicants state in
Claims 1-20 were allegedly not entitled to the benefit of the Priority Application.
Specifically, "data correction" and "difference time periods" in claim 1 and "histoimage"
in claim 10 were allegedly unsupported by the Priority Application. Applicant
respectfully disagrees.
The examiner agrees in part.
Thus claims 1,2,3,4,5,6,7,8,9, ,11,12 and 14,18,19,20,21,22,23,24 is given the benefit of the Priority Application while claim 10 with “histoimage” is not given the benefit of the Priority Application, filed 7/15/2024:
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II. Objection to the claims because of informalities
Applicant’s arguments, see remarks, filed 7/16/2026, with respect to the claim objection have been fully considered and are persuasive. The claim objection of claims 8 and 9 has been withdrawn.
Ill. Interpretation of claims in view of MPEP 2143.03
Applicant's arguments filed 7/16/2026 have been fully considered but they are not persuasive: Applicants state in page 19:
The Office Action applies the broadest reasonable interpretation ("BRI") to the pending claims and indicates that certain claim language does not positively limit the scope of the claims. In particular, the Office Action concludes that (i) limitations relating to correction of a preliminary PET parametric image need not be considered because the corrected image is recited as an alternative in claim 1, and (ii) language such as "determining whether" does not impose a positive limitation because it may render subsequent actions optional.
The examiner respectfully disagrees since claim 1 is written in the alternative:
1. (Currently Amended) A method for quality evaluations of parametric imaging in positron emission tomography (PET), implemented on a computing device having at least one processor and at least one storage device, the method comprising:
obtaining multiple PET images collected via a PET scan of a target subject, the PET images being dynamic PET images for difference time periods during the PET scan and used to generate a target PET parametric image of the target subject;
generating a preliminary PET parametric image by processing the PET images using at least one pharmacokinetic model;
performing a first quality evaluation on the PET images to generate a first evaluation result, the first quality evaluation including at least one of a first motion evaluation or a first noise level evaluation;
performing a second quality evaluation on the preliminary PET parametric image to generate a second evaluation result, the second quality evaluation including at least one of a second motion evaluation, a second noise level evaluation, or a pharmacokinetic model evaluation;
in response to determining that at least one of the first evaluation result or the second evaluation result indicates that data correction needs to be performed, correcting the PET images or [[a]] the preliminary PET parametric image, and generating the target PET parametric image of the target subject based on the corrected PET images or the corrected preliminary PET parametric image
Applicants state in page 20:
Firstly, Applicant respectfully disagrees with the Examiner's position that the
recitation "correcting the PET images or a preliminary PET parametric image" renders
certain limitations directed to the preliminary PET parametric image non-limiting. As
amended, claim 1 mandates the generation of a preliminary PET parametric image and
the performance of a second quality evaluation on that preliminary image as essential,
non-optional steps, and the dependent claims (e.g., claims 4-7) merely elaborate on
how those mandatory steps are carried out-e.g., model selection, motion/noise
evaluations, and matching assessment. Thus, the presence of two alternative
correction paths does not make the preceding generating and evaluating steps optional, nor does it deprive the dependent limitations of their further-limiting effect.
The examiner respectfully disagrees since said alternatives (“correcting the PET images or [[a]] the preliminary PET parametric image”) in claim 1 is “Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope1 of a claim under the broadest reasonable claim interpretation.” via MPEP 2143.03, 3rd paragraph:
2143.03 All Claim Limitations Must Be Considered [R-01.2024]
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
Exploring this concept of language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim (claim 1):
1. (Currently Amended) A method for quality evaluations of parametric imaging in positron emission tomography (PET), implemented on a computing device having at least one processor and at least one storage device, the method comprising:
obtaining multiple PET images collected via a PET scan of a target subject, the PET images being dynamic PET images for difference time periods during the PET scan and used to generate a target PET parametric image of the target subject;
generating a preliminary PET parametric image by processing the PET images using at least one pharmacokinetic model;
performing a first quality evaluation on the PET images to generate a first evaluation result, the first quality evaluation including at least one of a first motion evaluation or a first noise level evaluation;
performing a second quality evaluation on the preliminary PET parametric image to generate a second evaluation result, the second quality evaluation including at least one of a second motion evaluation, a second noise level evaluation, or a pharmacokinetic model evaluation;
in response to determining that at least one of the first evaluation result or the second evaluation result indicates that data correction needs to be performed,{{{ correcting the PET images or [[a]] the preliminary PET parametric image}}}, and generating the target PET parametric image of the target subject based on the corrected PET images or the corrected preliminary PET parametric image
Claims 2,3,4,5,6,8,9,10,11,12 is not affected by said language:
{{{correcting the PET images or [[a]] the preliminary PET parametric image}}}
while
Claims 7’s “the preliminary PET parametric image needs to e corrected” is affected by said language:
{{{ correcting the PET images or [[a]] the preliminary PET parametric image}}}.
Thus Markush alternative claim 7 can be taught if the other Markush alternative-correcting the PET images- is taught under the broadest reasonable interpretation of claims 1,4 and 7.
Applicants state in page 20:
Secondly, regarding the Examiner's concern about the recitation "determining
whether", Applicants have amended the claims to replace that language with affirmative
recitations of required processing steps. Applicants respectfully submit that the present
claim language clearly defines mandatory claim limitations and removes the ambiguity
identified by the Examiner.
The examiner agrees that the current claim set’s contingent limitations are limitations, namely in the system claim 14. Due to the amendment, the method claims 1 and 20 appear to be free of contingent limitations.
IV. Rejection under 35 U.S.C. § 101
Applicant’s arguments, see remarks, page 7, 1st para:
As discussed below, Applicants respectfully submit that the pending claims are
directed to specific technological improvements in positron emission tomography (PET)
parametric imaging and do not recite an abstract idea. Moreover, even assuming,
arguendo, that any portion of the claims involves a judicial exception, the claimed
inventions integrate any such exception into a practical application and further recite
significantly more than the alleged judicial exception.
, filed 7/16/2026, with respect to 35 USC 101 have been fully considered and are persuasive. The 35 USC 101 rejection of claims 1-20 has been withdrawn.
V. Rejection under 35 U.S.C. § 102(a)(1) based on Zheng
Applicant's arguments filed 7/16/2025 have been fully considered but they are not persuasive:
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 27, 5th para, last S “the "evaluate-before-act" pre-evaluation strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Regarding claim 1:
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 27, last para, last S “a specific dual evaluation mechanism”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 28, 4th para, last S “evaluates2 both: (1) the original PET images; and (2) the preliminary PET parametric image”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast claim 1 says:
“performing a first quality evaluation3 on4 the PET images”.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 28, last para, 1st S “a dual evaluation mechanism”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant’s arguments, see remarks, pages 28,29 last para:
However, Zheng does not disclose such a dual evaluation mechanism of claim 1.
In Zheng, the method proceeds directly to data correction without any preceding quality
evaluation. Specifically, Zheng performs attenuation correction on the PET scan data
(S110), then reconstructs a first parametric image (S120), directly filters the PET data to
obtain target PET data (S130), reconstructs a second parametric image (S140), and
finally uses a sparse matrix of the second parametric image to guide-filter the first
parametric image (S150) - see paragraphs [0066]-[0104] and FIG. 2. There is no step
of evaluating the quality of the original PET images or the preliminary parametric image,
let alone generating a first or second evaluation result based on motion, noise level, or pharmacokinetic model. Moreover, Zheng does not make any correction conditional on
an evaluation outcome; instead, it always applies noise filtering and guided filtering as
fixed procedural steps. Thus, Zheng fails to disclose, teach, or suggest the claimed
mechanism that first performs multi-dimensional evaluations on both the PET images
and the preliminary parametric image, and then corrects the data only when the
evaluation results indicate that correction is needed.
, filed 7/16/2026, with respect to the rejection(s) of claim(s) 1 under 35 USC 102(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein Koyama likewise teaches assess5 or determine quality via [0083], 4th S:
In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 28, last para, 3rd S “evaluating the quality”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast claim 1 says:
“performing a first quality evaluation6 on7 the PET images”.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 28, last para, last S “the claimed mechanism that first performs multi-dimensional evaluations on both the PET images and the preliminary parametric image”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Regarding claim 14:
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 30, 2nd para: “evaluating8 whether a pharmacokinetic model appropriately matches PET data at physical points”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast, claim 14 says:
“determining9 a matching degree of the pharmacokinetic model with respect to the physical point based on the PET images”.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 30, 3rd para: “the pharmacokinetic model evaluation and correction determination mechanism”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Regarding claim 20:
Applicant's arguments filed 7/16/2025 have been fully considered but they are not persuasive:
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 30, 4th para: “a preliminary evaluation step…."evaluate-before-act" strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast claim 20 says:
--performing a quality evaluation on the PET images by:10
for each of the PET images, generating an organ segmentation image by segmenting organs in the PET image;
determining motion information of the organs of the target subject based on the organ segmentation image corresponding to each of the PET images; and
in response to determining that the motion information indicates that there are one or more organs with displacements or motion fields greater than a displacement threshold, determining that motion correction is needed;--
Thus according to the above colon (of “performing a quality evaluation on the PET images by:”) the above entire portion itself is the claimed “performing a quality evaluation” with no clear following act-strategy.
Applicant’s arguments, pages 30,31 last paragraph:
In the Office Action on page 25, Examiner suggests that Zheng's kinetic
parameter matrix and Maroy's organ segmentation could be combined to arrive at the
claimed invention. However, Maroy is directed to pharmaco-organ segmentation for
pharmacokinetic analysis, based on tracer kinetics, and its purpose is to derive
time-activity curves for different pharmacokinetic compartments. Maroy does not
disclose determining motion information based on organ segmentation images, nor
does it teach or suggest using such motion information to pre-evaluate whether correction should be triggered. Therefore, claim 20 is novel and non-obvious over the
cited prior art.
with respect to claim(s) 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument:
Claim(s) 2 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of Jansen et al. (US 2021/0196219 A1), wherein Koyama teaches a PET brain segmentation binary bit-pattern mask, fig. 17:
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and wherein Jansen teaches a motion threshold in fig. 3:312:
Jansen teach the difference of claim 2 (including claim 20) of:
displacements
[0103] An example method for positron emission tomography (PET), comprises reconstructing image frames using emission data acquired in real-time while performing an emission scan of a patient; indicating patient motion in response to a displacement of the patient between image frames exceeding a threshold; and in response to the patient motion, performing one or more motion detection responses.).
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VI. Rejection under 35 U.S.C. § 103 based on Zheng and Maroy
Applicants state in page 31 of the remarks of 7/16/2026:
Claims 2, 3, 4, 5, 7 and 15, 16, 17, 18 stand rejected under 35 U.S.C. § 103 as
allegedly being unpatentable over Zheng in view of Maroy. Applicant respectfully
traverses the rejection.
In response:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1):
Claim(s) 2 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of Jansen et al. (US 2021/0196219 A1):
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of YOO et al. (US 2016/0300370 A1):
Applicant’s arguments, page 31 last paragraph:
As set forth above, Zheng fails to disclose each and every element of amended
claims 1 and 14. Applicant respectfully submits that Maroy does not remedy the deficiencies of Zheng set forth above with respect to amended claims 1 and 14.
Like Zheng, Maroy also does not disclose or suggest the "evaluate-before-act" strategy of amended claims 1 and 14. Accordingly, claims 1 and 14 are patentable under 35 § 103 over Zheng and Maroy.
with respect to claim(s) 2, 3, 4, 5, 7 and 15, 16, 17, 18 and 1 and 14 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument:
Claim(s) 2 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of Jansen et al. (US 2021/0196219 A1), wherein Koyama teaches a PET brain segmentation binary bit-pattern mask, fig. 17:
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and wherein Jansen teaches a motion threshold in fig. 3:312:
Jansen teach the difference of claim 2 (including claim 20) of:
displacements
[0103] An example method for positron emission tomography (PET), comprises reconstructing image frames using emission data acquired in real-time while performing an emission scan of a patient; indicating patient motion in response to a displacement of the patient between image frames exceeding a threshold; and in response to the patient motion, performing one or more motion detection responses.).
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In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 31, last para, 3rd S “evaluating11 the matching degree between a pharmacokinetic model and each physical point… assessing how well a model fits individual points…using such an assessment to decide whether to correct the model for that point”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast claim 14 says:
determining12 a matching degree of the pharmacokinetic model with respect to the physical point based on the PET images.
VII. Rejection under 35 U.S.C. § 103 based on Zheng, Maroy, and Mikhno
Applicants state in page 32, 5th para:
Claims 6 and 19 stand rejected under 35 U.S.C. § 103 as allegedly being
unpatentable over Zheng in view of Maroy as applied in claims 2, 3, 4, 5 and 15, 16, 17,
18, and further in view of Mikhno. Applicant respectfully traverses the rejection.
In response claims 6 and 19 are rejected under new art:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein claim 6 is written as a noise alternative that does not limit the scope of the claim under the broadest reasonable interpretation since a corresponding other motion correction alternative is already taught in claim 1:
6. (Currently Amended) The method of claim [[4]]1, wherein the second quality evaluation includes the second noise level evaluation, and the second noise level evaluation is performed by
for each physical point of the target subject,
determining a time-activity curve (TAC) of the physical point based on pixel values corresponding to the physical point in the PET images;
determining a noise level parameter corresponding to the physical point based on the TAC of the physical point; [[ and]]
determining a noise level of the preliminary PET parametric image based on the noise level parameter corresponding to each physical point and
in response to determining that the noise level of the preliminary PET parametric image is greater than a noise level threshold, determining that noise correction is needed .
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 32, 2nd para: “ ‘evaluate-before-act’ strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
VIII. Rejection under 35 U.S.C. § 103 based on Zheng, Maroy, and Wang
Applicants state in page 33:
Claim 8 stands rejected under 35 U.S.C. § 103 as allegedly being unpatentable
over Zheng in view of Maroy as applied in claims 2,3,4,5 and 15, 16, 17, 18, and further in view of Wang. Applicant respectfully traverses the rejection.
In response claim 8 is rejected under new art:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein claim 8 is not a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’ ”13:
8. (Currently Amended) The method of claim 4, wherein the determining a pharmacokinetic model corresponding to the physical point comprises:
determining a [[TAC]ltime-activity curve (TAC) of the physical point based on pixel values corresponding to the physical point in the PET images; and
selecting, from multiple candidate pharmacokinetic models, the pharmacokinetic model corresponding to the physical point based on the TAC of the physical point.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 33,4th para, last S: “ ‘evaluate-before-act’ strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
IX. Rejection under 35 U.S.C. § 103 based on Zheng, Maroy, Wang, and Liu
Applicants state in pages 33,34:
Claim 9 stand rejected under 35 U.S.C. § 103 as allegedly being unpatentable
over Zheng in view of Maroy as applied in claims 2,3,4,5 and 15, 16, 17, 18, further in view of Wang as applied in claim 8, and further in view of Liu. Applicant respectfully
traverses the rejection.
In response, claim 9 is rejected under new art:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein claim 9, like claim 8, is not a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’:
9. (Currently Amended) The method of claim 8, wherein the pharmacokinetic model corresponding to the physical point is determined by processing the TAC of the physical point using a selection model, the selection model being generated by training a preliminary model using training samples, each of the training samples corresponding to a sample physical point and being determined by:
determining a sample TAC of the sample physical point based on sample PET images collected in a sample PET scan of a sample subject;
determining predicted TACs of the sample physical point corresponding to the candidate pharmacokinetic models by processing the sample PET images using the candidate pharmacokinetic models;
determining a recommended pharmacokinetic model from the candidate pharmacokinetic models based on the sample TAC and the predicted TACs; and
designating the sample TAC as a training input of the training sample and the recommended pharmacokinetic model as a training label of the training sample.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 34,2nd para, last S: “ ‘evaluate-before-act’ strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
X. Rejection under 35 U.S.C. § 103 based on Zheng and Panin
Applicants state in page 34:
Claim 10 stands rejected under 35 U.S.C. § 103 as allegedly being unpatentable
over Zheng in view of Panin. Applicant respectfully traverses the rejection.
In response, claim 9 is rejected under new art:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein claim 10, like claims 8 and 9, is not a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’:
10. (Currently Amended) The method of claim 1, wherein the method further comprises:
obtaining sets of PET raw data collected in the PET scan, the PET images being reconstructed from the sets of PET raw data;
for each set of PET raw data, generating a histoimage corresponding to the set of PET raw data;
determining motion information of organs of the target subject based on the histoimage corresponding to each set of PET raw data; and
in response to determining that the motion information indicates that the target subject has an obvious movement or deformation during the PET scan, determining that motion correction is needed .
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 34,6th para, last S: “ ‘evaluate-before-act’ strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
XI. Rejection under 35 U.S.C. § 103 based on Zheng and Cheng
Applicants state in page 35:
Claims 11 and 12 stand rejected under 35 U.S. C. § 103 as allegedly being
unpatentable over Zheng in view of Cheng. Applicant respectfully traverses the
rejection.
In response, claims 11 and 12 is rejected under new art:
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1), wherein claims 11 or 12, like claims 8 and 9 and 10, is not a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’:
11. (Currently Amended) The method of claim 1, wherein the method further
obtaining sets of PET raw data collected in the PET scan, the PET images being reconstructed from the sets of PET raw data;
for each set of PET raw data,
determining a coincidence event count based on the set of PET raw data;
determining a noise level parameter of the set of PET raw data based on the coincidence event count corresponding to the set of PET raw data;
determining a total noise level parameter of the sets of PET raw data based on the noise level parameter of each set of PET raw data: and
in response to determining that the total noise level parameter is greater than a noise level parameter threshold, determining that noise correction is needed
12. (Original) The method of claim 1, wherein the obtaining multiple PET images collected in a PET scan of the target subject comprises:
obtaining multiple sets of PET raw data collected in the PET scan;
for each set of PET raw data,
determining coincidence event count based on the set of PET raw data;
determining a reconstruction algorithm for reconstructing the set of PET raw data based on the coincidence event count; and
generating the PET images by reconstructing the sets of PET raw data using their respective reconstruction algorithms.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 35, 3rd para, last S: “ ‘evaluate-before-act’ strategy”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
XII. New claims
Applicants state in page 35:
Newly added claims 21-24 depend directly or indirectly from amended claim 14,
thus are also patentable for at least the same reasons as stated above with respect to
independent claim 14, and for the additional features recited therein.
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1),
wherein claims 21,24,23 is not a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’.
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of XIE et al. (US 2020/0342592 A1), wherein claim 22:
22. (New) The system of claim 21, wherein the correcting the preliminary PET parametric image includes:
determining target physical points of the target subject whose determination result indicates that the corresponding pixel needs to be corrected;
for each target physical point, determining a new pharmacokinetic model corresponding to the target physical point, and determining a new PET parametric value of the target physical point based on the pixel values corresponding to the target physical point in the PET images using the new pharmacokinetic model; and
correcting the preliminary PET parametric image by updating the PET parametric values of the target physical points in the preliminary parametric image with their new PET parametric values.
is a “limitation in a claim… where the clause gave ‘meaning and purpose to the manipulative steps’ thus XIE teaches the claim limitation (i.e., the difference of claim 22) of claim 22:
XIE teach the difference of claim 22 of:
updating (the of the14)15 with their 16 parametric values (or likewise updating a parameter via [0137] and fig. 5:520: “Determining a regularization parameter”:
[0137] In some embodiments, the image reconstruction process may include a plurality of iterations. In each of the plurality of iterations, a PET image reconstructed in a prior iteration may be updated based on the objective function configured with the regularization parameter. In some embodiments, the boundary information of structures of the subject may be updated based on a reconstructed PET image in each iteration. In this case, the regularization parameter may also be updated in the plurality of iterations.
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).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1):
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Re 1. (Currently Amended), ZHENG teaches A method for quality evaluations of parametric imaging in positron emission tomography (PET)17, implemented on a computing device having at least one processor and at least one storage device, the method comprising18 (likewise):
obtaining multiple PET images (or “PET data”, pg. 9, 6th txt blk) collected via a PET scan of a target19 subject (or “to20 the patient”, pg. 2, 4th txt blk), the PET images being dynamic PET images (or “PET imaging comprises…dynamic PET imaging”, pg. 2, 4th txt blk) for difference time periods2122 (or “the long-time signal23 collection”, pg. 2, last txt blk, wherein the signal comprises different periods of time) during the PET scan and used to generate a target PET parametric image24 (or “reconstruct the parameter image of the PET data”, pg. 3, 4th txt blk) of the target subject;
generating a preliminary PET parametric image (in the role, function or status of a map) by processing the PET images (or likewise generating a fused map via “In this embodiment, the two images25 can be fused, so that the obtained target PET parameter image has better image quality.”, ZHENG, machine translation II, pg. 17, 6th txt blk) using a {{{pharmacokinetic26}}} model272829 (or likewise a visible, drug, gamma-camera, absorption, distribution model/image/delineation via “a drug…tracer30 distribution map31”, ZHENG, machine translation II, pg. 3, 1st txt blk)32;
performing a first {{{quality}}} evaluation on the PET images to generate a first {{{evaluation}}} result , the first {{{quality}}} evaluation including {{{at least one of}}} a first {{{motion}}} evaluation {{{or a first noise level evaluation}}};
performing a second {{{quality}}} evaluation on the preliminary PET parametric image to generate a second {{{evaluation}}} result, the second {{{quality}}} evaluation including {{{at least one of}}} a second {{{motion}}} evaluation {{{, a second noise level evaluation, or a pharmacokinetic model evaluation}}};
in response to determining that {{{at least one of}}} the first {{{evaluation}}} result {{{or the second evaluation result}}} indicates that data correction needs to be performed33, correcting the PET images (or said likewise “PET scanning data can be…corrected34”, pg. 10, 2nd txt blk) {{{or35 [[a]] the preliminary PET parametric image}}}36, and
generating the target PET parametric image of the target subject based on (via fig. 2, translated below) the corrected PET images (fig. 2: S110: “Attenuation correction was performed on the PET scan data to obtain the PET data”)
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ZHENG does not teach, including the narrow subset of claim scope, the difference of claim 1 of:
(performing a first quality)37 evaluation (on the PET images) to generate a first evaluation result , the first quality evaluation including at least one of a first motion evaluation or a first noise level evaluation;
performing a second quality evaluation (on the preliminary PET parametric image) to generate a second evaluation result, the second quality evaluation including at least one of a second motion evaluation, a second noise level evaluation, or a pharmacokinetic model evaluation;…
(in response to determining that) at least one of the first evaluation result or the second evaluation result indicates that (data correction needs to be performed, correcting the PET images).
Koyama teach the difference of claim 1 of:
(performing a first quality)38 evaluation (on the PET images) to generate a first evaluation result , the first quality evaluation including at least one of a first motion evaluation {{{
performing a second quality evaluation (on the preliminary PET parametric image) to generate a second evaluation result, the second quality evaluation including at least one of a second motion evaluation {{{…
(in response to determining that) at least one of the first evaluation result or the second evaluation result indicates that (data correction needs to be performed, correcting the PET images) (or likewise “In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio).” [0083], 4th S, as shown in fig. 17:
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)
Since ZHENG suggests improving brain image quality with a possible image quality correction via ZHENG, machine translation II, pg. 13, 2nd txt blk:
“In order to improve the PET imaging quality, in this embodiment, the PET scanning39 data can be attenuated and corrected. wherein the attenuation correction process can be represented by the following formula:”
one of skill in the art could or would have done is refer to the other possibilities of brain image quality correction and thus make ZHENG’s be as Koyama’s seeing in the change an increase in a desired PET signal via Koyama’s [0083]:
“[0083] In some embodiments, amyloid plaque load can be identified by a standard uptake value ratio (SUVr) as compared to a reference region. Methods for calculating PET SUVr are known in the art and may include those described herein. In some embodiments, a Standard Uptake Value Ratio Quantitative analysis of amyloid levels is completed using PMOD Biomedical Image Quantification Software (PMOD Technologies, Zurich, Switzerland). In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio)40. In some embodiments, corresponding MRIs from subjects are prepared (e.g., using matrix size reduction processing, cropping of the MRI to include only the brain, segmentation to separate images into binary maps of gray matter, white matter, and CSF, and stripping the image of skull leaving only brain mask). In some embodiments, the averaged PET images and prepared MRIs are matched using the PMOD Matching Function, placing the images in the same orientation. In some embodiments, a Brain Normalization function, e.g., as provided by PMOD software, is used along with Brain Norm and Rigid Matching transformation matrices, to produce an averaged PET. In some embodiments, this averaged PET which is normalized to the MNInst space (Senjem et al, 2005) that is in the same orientation as the subject's segmented MRI for quantitative analysis. In some embodiments, the PMOD Mask Function is used to mask the brain and zero the image outside of the mask to create a Normalized Gray Matter PET and a Normalized White Matter PET. Standard uptake values (SUVs) may be calculated for all gray matter mapped regions and the 3 white matter regions (pons, cerebellar white, and subcortical white) using PMOD software calculated using the normalized PET, subject weight, and injected dose of tracer to arrive at the units of SUVs. In some embodiments, the SUVr is the ratio of the global cortical average as compared to a reference region of choice. In some embodiments, a whole cerebellum mask is used as the reference region. In some embodiments, the reference region is subcortical white matter, derived whole cerebellum, whole cerebellum adjusted by subcortical white matter, cerebellar gray matter, and composite reference regions consisting of cerebellar cortex, pons subcortical white matter, and cerebella white matter.”
via creative, explicit, routine, inferential Supreme Court steps, A,B,C:
A) Create a Target Image Obtaining Program based on ZHENG’s fig. 2:
A1) at step S110 create code calling/returning from a motion-correction PMOD Biomedical Image Quantification Software:
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B) run said Target Image Obtaining Program calling said motion-correction PMOD Biomedical Image Quantification Software;
C) see what happens (I foresee goodness or an increase in a desired PET attenuation signal at said attenuation correction step S110:
“[0083] In some embodiments, amyloid plaque load can be identified by a standard uptake value ratio (SUVr) as compared to a reference region. Methods for calculating PET SUVr are known in the art and may include those described herein. In some embodiments, a Standard Uptake Value Ratio Quantitative analysis of amyloid levels is completed using PMOD Biomedical Image Quantification Software (PMOD Technologies, Zurich, Switzerland). In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio)41. In some embodiments, corresponding MRIs from subjects are prepared (e.g., using matrix size reduction processing, cropping of the MRI to include only the brain, segmentation to separate images into binary maps of gray matter, white matter, and CSF, and stripping the image of skull leaving only brain mask). In some embodiments, the averaged PET images and prepared MRIs are matched using the PMOD Matching Function, placing the images in the same orientation. In some embodiments, a Brain Normalization function, e.g., as provided by PMOD software, is used along with Brain Norm and Rigid Matching transformation matrices, to produce an averaged PET. In some embodiments, this averaged PET which is normalized to the MNInst space (Senjem et al, 2005) that is in the same orientation as the subject's segmented MRI for quantitative analysis. In some embodiments, the PMOD Mask Function is used to mask the brain and zero the image outside of the mask to create a Normalized Gray Matter PET and a Normalized White Matter PET. Standard uptake values (SUVs) may be calculated for all gray matter mapped regions and the 3 white matter regions (pons, cerebellar white, and subcortical white) using PMOD software calculated using the normalized PET, subject weight, and injected dose of tracer to arrive at the units of SUVs. In some embodiments, the SUVr is the ratio of the global cortical average as compared to a reference region of choice. In some embodiments, a whole cerebellum mask is used as the reference region. In some embodiments, the reference region is subcortical white matter, derived whole cerebellum, whole cerebellum adjusted by subcortical white matter, cerebellar gray matter, and composite reference regions consisting of cerebellar cortex, pons subcortical white matter, and cerebella white matter.”
Re 3., ZHENG of the combination of ZHENG-Koyama teaches The method of claim 1, {{{wherein the first quality evaluation includes the first noise level evaluation, and the first noise level evaluation is performed by
for each of the PET images, determining, in the PET image, a target region corresponding to a target organ;
determining a variation (via a “transform algorithm…calculation formula”, pg. 12, 1st txt blk) of pixel values (or likewise “the voxel in the guide image”, pg. 13, 8th txt blk) in the target region;
determining a total variation of the PET images based on the variations corresponding to the PET images and
in response to determining that the total variation is greater than a variation threshold, determining that noise correction is needed 42.
Re 4. (Currently Amended), ZHENG of the combination of ZHENG-Koyama teaches The method of claim 1, {{{wherein43 the generating a preliminary PET parametric image by processing the PET images using at least one pharmacokinetic model comprises
for each physical point (or likewise “the voxel44 in the guide image”, pg. 13, 8th txt blk) of the target subject, determining a pharmacokinetic model corresponding to the physical point (or likewise “obtain the target PET parameter image…as…the…matrix… voxel45”, ZHENG, machine translation II, pg. 18, 1st txt blk, in fig. 2: S150: “obtain the target PET parameter image”:
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) ; and
determining a PET parametric value (likewise resulting in a “calculated” “parameter image”, pg. 11, 2nd txt blk) of the physical point based on pixel values (or likewise “voxel”-“information46”, pg. 13, 9th txt blk) corresponding to the physical point in the corrected PET images or47 the PET images using the pharmacokinetic model of the physical point; and
generating the preliminary PET parametric image based on the PET parametric value of each physical point of the target subject}}}.
Re 7.48 (Currently Amended) , ZHENG of the combination of ZHENG-Koyama teaches The method of claim 4,
{{{wherein49 the second quality evaluation includes the pharmacokinetic model evaluation50, and the pharmacokinetic model evaluation is performed by
for each physical point of the target subject, determining a matching degree (or likewise a “block-matching”, “BM3D”, in “the formula corresponding to the inverse transformation algorithm”, ZHENG, pg. 12, 2nd txt blk: [0092] of CN 112652029 A:
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) of the pharmacokinetic model with respect to the physical point based on the corrected PET images or the PET images51;
generating a determination result (via said block-matching formula) indicating whether52 the corresponding pixel of the physical point in the preliminary PET parametric image needs to be corrected based on the matching degree; and
in response to determining that a count of physical points whose corresponding pixels need to be corrected is greater than a count threshold, determining that pharmacokinetic model correction is needed .
Re 8., ZHENG of the combination of ZHENG-Koyama teaches The method of claim 4, {{{wherein the determining a pharmacokinetic model corresponding to the physical point comprises:
determining a [[TAC]] time-activity curve (TAC) of the physical point based on pixel values (or likewise “the voxel53 in the guide image”, ZHENG, pg. 13, 8th txt blk) corresponding to the physical point in the PET images; and
selecting, from multiple candidate pharmacokinetic models, the pharmacokinetic model corresponding to the physical point based on the TAC of the physical point}}}54.
Re 9. (Currently Amended), ZHENG of the combination of ZHENG-Koyama teaches The method of claim 8,
{{{wherein55 the pharmacokinetic model corresponding to the physical point is determined by processing the TAC of the physical point using a selection model (or likewise said “The three models”, WANG [0177]), the selection model being generated by training a preliminary model (or likewise said “The three models”, WANG [0177]) using training samples, each of the training samples corresponding to a sample physical point5657 (or likewise “the voxel58 in the guide image”, ZHENG, pg. 13, 8th txt blk) and being determined by:59
determining a sample TAC of the sample physical point based on sample PET images60 collected in a sample PET scan61 of a sample subject (or likewise “the patient”, ZHENG, pg. 2, 4th txt blk);62
determining predicted TACs of the sample physical point corresponding to the
candidate pharmacokinetic (“models of a pharmacokinetics. organ”, MAROY pg. 17, 2nd txt blk) models by processing the sample PET images using the candidate pharmacokinetic models;
determining a recommended pharmacokinetic model6364 (“models of a pharmacokinetics. organ”, MAROY pg. 17, 2nd txt blk) from the candidate pharmacokinetic models based on the sample TAC and the predicted TACs; and
designating65 (or likewise said selection of “The three models”, WANG [0177]) the sample TAC as a training input (likewise “information”66, ZHENG, pg. 11, 3rd txt blk) of the training sample and the recommended pharmacokinetic model as a training label of the training sample}}}.
Re 6. (Currently Amended), ZHENG of the combination of ZHENG-Koyama teaches The method of claim [[4]] 1, {{{wherein the second quality evaluation includes the second noise level evaluation, and the second noise level evaluation is performed by
for each physical point (or likewise “the voxel67 in the guide image”, pg. 13, 8th txt blk) of the target subject, determining a time-activity curve (TAC) of the physical point based on pixel values corresponding to the physical point in the PET images;
determining a noise level parameter corresponding to the physical point based on the TAC of the physical point; [[and]]
determining a noise level of the preliminary PET parametric image based on the noise level parameter corresponding to each physical point and
in response to determining that the noise level of the preliminary PET parametric image is greater than a noise level threshold, determining that noise correction is needed
Re 10. (Currently Amended), ZHENG teaches The method of claim 1, wherein68 the method further comprises:
obtaining (matrix) sets of PET69 raw70 data717273 (or likewise “analog”74- “PET scanning data”, pg. 9, last txt blk) collected in the PET scan, the PET images being reconstructed (via “the parameter image reconstruction process” “after the PET scanning data is attenuated and corrected”, pg. 10, 5th txt blk) from the sets of PET raw data;
for each set of PET raw data, generating a histoimage corresponding to the set of PET raw data;
determining motion information (or likewise “a kinetic parameter matrix” “A”, pg. 11, 1st txt blk, multiplied with “PET data” “y”, pg. 11, 1st txt blk: [0076] of original published CN 112652029 A:
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) of organs of the target subject based on the histoimage corresponding to each set of PET raw data; and
in response to determining that the motion information indicates that the target subject has an obvious movement or deformation during the PET scan, determining that motion correction is needed
Claim 11 is rejected/interpreted like claim 10:
Re 11., ZHENG teaches The method of claim 1, {{{wherein the method further
obtaining (“matrix”, pg. 11, 2nd para) sets of PET raw data75 (or likewise said “analog”-“PET scanning data”, pg. 9, last txt blk) collected in the PET scan, the PET images being reconstructed from the sets of PET raw data;
for each set of PET raw data,
determining a coincidence event76 count based on the set of PET raw data;
determining a noise level7778 parameter (or likewise a “signal-to-noise ratio79”, pg. 8,1st txt blk) of the set of PET raw data based on the coincidence event count corresponding to the set of PET raw data;
determining a total noise level parameter of the sets of PET raw data based on the noise level parameter of each set of PET raw data: and
in response to determining that the total noise level parameter is greater than a noise level parameter threshold, determining that noise correction is needed
Claim 12 is rejected like claim 11:
Re 12. (Original), ZHENG of the combination of ZHENG-Koyama teaches The method of claim 1, {{{wherein80 the obtaining multiple PET images collected in a PET scan of the target subject comprises:
obtaining multiple sets of (A) PET (B) raw data (“PET raw data” is interpreted as “PET data” OR “raw data”) collected in the PET scan;
for each set of (A) PET (B) raw data, determining coincidence event count based on the set of (A) PET (B) raw data;
determining a (“preset parameter image”, pg. 10, 6th txt blk) reconstruction algorithm for reconstructing the set of (A) PET (B) raw data based on the coincidence event count; and
generating the PET images by reconstructing the sets of PET raw data using their respective reconstruction algorithms (or likewise “the parameter image reconstruction image reconstruction algorithm, can be… maximum posterior probability algorithm (Maximum A Posterior, MAP); expectation maximization (Expectation Maximization, EM) algorithm and so on”, pg. 10, last txt blk)}}}.
Claim 14 rejected/interpreted like claim 1:
Re 14. (Currently Amended), ZHENG of the combination of ZHENG-Koyama teaches A system for quality evaluations of parametric imaging in positron emission tomography (PET)81, comprising:
at least one storage device including a set of instructions; and
at least one processor in communication with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to direct the system to perform operations including82:
obtaining multiple PET images (or likewise at fig. 2: “S140… obtain the second PET parameter image”, ZHENG, machine translation II, pg. 17, 2nd txt blk) collected via a PET scan of a target subject, the PET images being dynamic PET images (or likewise at fig. 2:S110 perform “tracer”-“PET imaging”, ZHENG: machine translation II, pg. 12, last txt blk) for {{{difference}}} time periods (or likewise “of continuous time83 point”, pg. 3, ZHENG, machine translation II, pg. 3, 1st txt blk) during the PET scan and used to generate a target PET parametric image84 of the target subject;
for each physical (voxel/pixel) point of the target subject,
determining a pharmacokinetic model (i.e., said tracer PET image of fig. 2:S110) corresponding to the physical point, and
determining a PET parametric value of the physical point based on pixel values corresponding to the physical point in the PET images using the pharmacokinetic model of the physical point (or said likewise at fig. 2:S150: “obtain the target PET parameter image… as… the … matrix… voxel85” of the second PET parameter image of voxels/pixels from S140, ZHENG, machine translation II, page 18, 1st txt blk, in fig. 2: S150: “obtain the target PET parameter image”);
generating a preliminary PET parametric image (before the final target PET parameter image) based on the PET parametric value of each physical point of the target subject (or likewise at fig. 2: “S140… obtain the second PET parameter image”, ZHENG, machine translation II, pg. 17, 2nd txt blk);
performing a quality evaluation on the preliminary PET parametric image by:
for each physical point of the target subject,
determining a matching degree (or likewise at fig. 2 step S130, sub-step S132: “adopt… matching… scale”, Zheng, machine translation, pg. 16, 5th txt blk) of the pharmacokinetic model with respect to the physical point based on the PET images, and
generating a determination result indicating (or likewise “S150, determining the sparse matrix of the second PET parameter image”, ZHENG, machine translation II, pg. 17, 5th txt blk) whether the86 corresponding pixel87 (or likewise the 2nd parametric image’s voxels equal the target parametric image via “the target PET parameter image… comprises…the voxel in the guide image (i.e., θ TD)”, ZHENG, machine translation II, page 18. 1st txt blk) of the physical point in the preliminary PET parametric image needs to be corrected88 based on the (scale) matching degree; and89
in response to determining that a count of physical points whose corresponding pixels need to be corrected is greater than a count threshold,
determining that pharmacokinetic model correction needs to be performed}}},
correcting the preliminary PET parametric image (or said likewise “PET scanning data can be…corrected90”, pg. 13, 2nd txt blk), and
generating the target PET parametric image of the target subject based on
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Claim 19 is rejected like claim 6:
Re 19. (Currently Amended), ZHENG of the combination of ZHENG-Koyama teaches The system of claim [[17]]14, {{{wherein91 the quality evaluation92 on the preliminary PET parametric image further 93 comprises:
for each physical point of the target subject,
determining94 a time-activity curve (TAC) of the physical point based on pixel values corresponding to the physical point in the PET images;
determining a noise level parameter corresponding to the physical point based on the TAC of the physical point; [[ and]]
determining a noise level of the preliminary PET parametric image based on the noise level parameter corresponding to each physical point; and
in response to determining that the noise level of the preliminary PET parametric image is greater than a noise level threshold, determining that noise correction is needed
Re 21. (New), ZHENG of the combination of ZHENG-Koyama teaches The system of claim 14, {{{wherein95 the determining a matching degree of the pharmacokinetic model with respect to the physical point based on the PET images comprises:
determining a first time-activity curve (TAC) of the physical point based on the pixel values corresponding to the physical point in the PET images;
determining a second TAC of the physical point based on the pixel values corresponding to the physical point in the PET images and the pharmacokinetic model corresponding to the physical point; and
determining the matching degree based on a similarity between the first TAC and the second TAC}}}.
Re 24. (New), ZHENG and Koyama of the combination of ZHENG-Koyama teaches The system of claim 21, {{{
96.
Re 23. (New), ZHENG and Koyama of the combination of ZHENG-Koyama teaches The system of claim 14, {{{
97.
Claim(s) 2 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of Jansen et al. (US 2021/0196219 A1):
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Re 2. (Currently Amended), ZHENG and Koyama of the combination of ZHENG-Koyama already teaches The method of claim 1, wherein the first quality evaluation includes the first motion evaluation, and the first motion evaluation is performed by
for each of the PET images, generating an organ (brain) segmentation image by segmenting organs (brains) in the PET image (or likewise “In some embodiments, the PMOD Mask Function is used to mask the brain and zero the image outside of the mask to create a Normalized Gray Matter PET and a Normalized White Matter PET.” Koyama [0083] 9th S);
determining motion information (or likewise “y represents PET data” multiplied/divided by “a kinetic98 parameter matrix”, pg. 11, 2nd txt blk, via the original publication of CN 112652029 A:
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) of the organs of the target subject based on the organ segmentation image corresponding to each of the PET images; and
in response to determining that the motion information indicates that one organ{{{s}}} (brain) with displacements or motion fields greater than a displacement threshold , determining that motion correction is needed (via said “In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio).”, Koyama [0083] 4th S).
ZHENG of the combination of ZHENG-Koyama does not teach the difference of claim 2 of:
displacements or motion fields greater than a displacement threshold.
Jansen teach the difference of claim 2 of:
displacements
[0103] An example method for positron emission tomography (PET), comprises reconstructing image frames using emission data acquired in real-time while performing an emission scan of a patient; indicating patient motion in response to a displacement of the patient between image frames exceeding a threshold; and in response to the patient motion, performing one or more motion detection responses.).
Since ZHENG teaches a problem reconstructing PET images, ZHENG, machine translation II, page 3, 2nd txt blk:
However, the long-time signal collection can not be avoided to improve the noise; In addition, large dose of radioactive medicine will cause irreversible damage to human body. Therefore, under the restriction of the collecting time and injection medicine dosage, dynamic PET reconstructed image signal-to-noise ratio is low. and the excessive noise will not display the actual condition of the patient, so that the difficulty of the medical diagnosis is increased, and the precision is reduced. Therefore, reducing imaging noise, improving the imaging quality, with important meaning in scientific research and clinical diagnosis.
one of skill in the art could or would have done is consult others for the fix and thus make ZHENG’s be as Jansen’s seeing in the change goodness via Jansen’s teaching of real-time PET reconstruction at [0008] and as shown in fig. 3:
[0008] FIG. 3 shows a high-level flow chart of an example method for performing PET-computed tomography with real-time99 PET image reconstruction to detect and respond to patient motion, according to an embodiment of the disclosure.
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Claim 20 is rejected/interpreted like claims 1,14 and 2:
Re 20., ZHENG of the combination of ZHENG-Koyama-Jansen teaches A non-transitory computer readable medium100, comprising at least one set of instructions for quality evaluations of parametric imaging in positron emission tomography (PET)101,
wherein when executed by one or more processors of a computing device, the at least one set of instructions causes the computing device to perform a method102, the method comprising:
obtaining multiple PET images collected via a PET scan of a target subject, the PET images being dynamic PET images for difference time periods during the PET scan and used to generate a target PET parametric image103 of the target subject;
performing a quality evaluation on the PET images by:
for each of the PET images, generating an organ (brain) segmentation image by segmenting organs in the PET image (or likewise “In some embodiments, the PMOD Mask Function is used to mask the brain and zero the image outside of the mask to create a Normalized Gray Matter PET and a Normalized White Matter PET.” Koyama [0083] 9th S);
determining motion information (or likewise “a kinetic104 parameter matrix”-“algorithm”105, ZHENG, machine translation II, pg. 14, last txt blk) of the organs of the target subject based on the organ segmentation image corresponding to each of the PET images; and
in response to determining that the motion information indicates that there are one or more organs with displacements or motion fields greater than a displacement threshold , determining that motion correction is needed106;
correcting the PET images
generating the target PET parametric image of the target subject based on the corrected PET images
{{{wherein107 the correcting the PET images includes:
correcting motion artifacts in the PET images using a motion artifact correction algorithm , or
registering each of the PET images with a reference image}}} .
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of YOO et al. (US 2016/0300370 A1):
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Re 5. (Currently Amended), ZHENG and Koyama of the combination of ZHENG-Koyama teaches The method of claim [[4]] 1 ,
wherein108 {{{the preliminary PET parametric image includes109 a first preliminary PET parametric image and a second preliminary PET parametric image corresponding to different PET parameters}}} , the second quality evaluation includes the second motion evaluation, and the second motion evaluation is performed by
determining a first {{{lesion segmentation}}} result by segmenting {{{lesion}}} areas (via said binary bit-pattern brain mask of Koyama) {{{from the first preliminary PET parametric image}}};
determining a second {{{lesion segmentation}}} result by segmenting lesion areas (via said binary bit-pattern brain mask of Koyama) {{{from the second preliminary PET parametric image}}};
determining a similarity (or likewise (1) ZHENG’s “three-dimensional block matching filtering algorithm”, machine translation II, pg. 5, 4th txt blk & (2) Koyama’s “ averaged PET images and prepared MRIs are matched using the PMOD Matching Function, placing the images in the same orientation. In some embodiments, a Brain Normalization function, e.g., as provided by PMOD software, is used along with Brain Norm and Rigid Matching transformation matrices, to produce an averaged PET. “ [0083], 6th & 7th Ss) between110 (via the 35 USC 103 combination of ZHENG-Koyama) the first {{{lesion segmentation}}} result and the second {{{lesion segmentation}}} result; and
in response to determining that the similarity is smaller than a similarity threshold, determining that motion correction is needed (via said “In some embodiments, PET images are first assessed for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio).”, Koyama [0083] 4th S)
ZHENG and Koyama of the combination of ZHENG-Koyama does not teach the difference of claim 5 of:
in response to determining that (the similarity)111 is smaller than a similarity threshold, (determining that motion correction is needed).
YOO teach the difference of claim 5 of:
in response to determining that (the similarity)112 is smaller than a similarity threshold, (determining that motion correction is needed) (in fig. 16:1610: “SIMILARITY… THRESHOLD”): 1640: “PEFORM MOTION CORRECTION”:
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).
Since Koyama suggests, if desired/needed, assessing a mathematical function’s point (X,Y,Z) at which motion correction is performed (i.e., a threshold)113 via [0083]:
[0083] In some embodiments, amyloid plaque load can be identified by a standard uptake value ratio (SUVr) as compared to a reference region. Methods for calculating PET SUVr are known in the art and may include those described herein. In some embodiments, a Standard Uptake Value Ratio Quantitative analysis of amyloid levels is completed using PMOD Biomedical Image Quantification Software (PMOD Technologies, Zurich, Switzerland). In some embodiments, PET images are first assessed114 for subject movement in the X, Y, and Z planes and corrected for motion, if needed, before individual images (e.g., 5-minute emission frames) are averaged, e.g., using a PMOD Averaging Function (PET frames averaged to increase the signal to noise ratio). In some embodiments, corresponding MRIs from subjects are prepared (e.g., using matrix size reduction processing, cropping of the MRI to include only the brain, segmentation to separate images into binary maps of gray matter, white matter, and CSF, and stripping the image of skull leaving only brain mask). In some embodiments, the averaged PET images and prepared MRIs are matched using the PMOD Matching Function, placing the images in the same orientation. In some embodiments, a Brain Normalization function, e.g., as provided by PMOD software, is used along with Brain Norm and Rigid Matching transformation matrices, to produce an averaged PET. In some embodiments, this averaged PET which is normalized to the MNInst space (Senjem et al, 2005) that is in the same orientation as the subject's segmented MRI for quantitative analysis. In some embodiments, the PMOD Mask Function is used to mask the brain and zero the image outside of the mask to create a Normalized Gray Matter PET and a Normalized White Matter PET. Standard uptake values (SUVs) may be calculated for all gray matter mapped regions and the 3 white matter regions (pons, cerebellar white, and subcortical white) using PMOD software calculated using the normalized PET, subject weight, and injected dose of tracer to arrive at the units of SUVs. In some embodiments, the SUVr is the ratio of the global cortical average as compared to a reference region of choice. In some embodiments, a whole cerebellum mask is used as the reference region. In some embodiments, the reference region is subcortical white matter, derived whole cerebellum, whole cerebellum adjusted by subcortical white matter, cerebellar gray matter, and composite reference regions consisting of cerebellar cortex, pons subcortical white matter, and cerebella white matter.
one of skill in the art could or would as desired referred to others as the fix and thus make Koyama’s of the combination of ZHENG-Koyams be as YOO’s seeing in the change goodness via YOO’s fig. 16:1660: “DE-BLURRING” :
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Claim 18 is rejected like claim 5:
Re 18., ZHENG of the combination of ZHENG-Koyama-YOO teaches The system of claim [[17]] 14 ,
wherein the preliminary PET parametric image includes a first preliminary PET parametric image and a second preliminary PET parametric image corresponding to different PET parameters, and
the quality evaluation on the preliminary PET parametric image further
determining a first lesion segmentation result by segmenting lesion areas from the first preliminary PET parametric image;
determining a second lesion segmentation result by segmenting lesion areas from the second preliminary PET parametric image;
determining a similarity between the first lesion segmentation result and the second lesion segmentation result; and
in response to determining that the similarity is smaller than a similarity threshold, determining that motion correction is needed .
Claim(s) 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZHENG et al. (CN 112652029 A) with SEARCH machine translation plus SEARCH machine translation II further in view of Koyama et al. (US 2024/0352109 A1) as applied in claims 1,3,4,7,8,9,6,10,11,12 and 14,19,21,24,23 further in view of XIE et al. (US 2020/0342592 A1):
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Re 22. (New), ZHENG and Koyama of the combination of ZHENG-Koyama teaches The system of claim 21, wherein115 the correcting the
determining st txt blk) points of the target subject whose determination result indicates that the116 corresponding (voxel) pixel117 (i.e., pixel values, i.e., an image made of pixels, i.e., an image made of voxels) needs to be (motion) corrected (via the combination of ZHENG-Koyama of the 35 USC 103 rejection of claim 14 at fig. 2 step S110, reproduced below);
{{{for each
determining a
determining a 118; and
correcting the image (via said the combination of ZHENG-Koyama of the 35 USC 103 rejection of claim 14 at fig. 2 step S110, reproduced below) by updating the PET values of the with their .
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ZHENG and Koyama of the combination of ZHENG-Koyama does not teach the difference of claim 22 of:
updating (the PET parametric values of the target physical points in the preliminary parametric image)119 with their new PET parametric values.
XIE teach the difference of claim 22 of:
updating (the of the120)121 with their 122 parametric values (or likewise updating a parameter via [0137] and fig. 5:520: “Determining a regularization parameter”:
[0137] In some embodiments, the image reconstruction process may include a plurality of iterations. In each of the plurality of iterations, a PET image reconstructed in a prior iteration may be updated based on the objective function configured with the regularization parameter. In some embodiments, the boundary information of structures of the subject may be updated based on a reconstructed PET image in each iteration. In this case, the regularization parameter may also be updated in the plurality of iterations.
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).
Since ZHENG teaches a problem reconstructing PET images, ZHENG, machine translation II, page 3, 2nd txt blk:
However, the long-time signal collection can not be avoided to improve the noise; In addition, large dose of radioactive medicine will cause irreversible damage to human body. Therefore, under the restriction of the collecting time and injection medicine dosage, dynamic PET reconstructed image signal-to-noise ratio is low. and the excessive noise will not display the actual condition of the patient, so that the difficulty of the medical diagnosis is increased, and the precision is reduced. Therefore, reducing imaging noise, improving the imaging quality, with important meaning in scientific research and clinical diagnosis.
one of skill in the art could or would have done is consult others for the fix and thus make ZHENG’s be as XIE’s seeing in the change goodness via XIE’s [0137]:
[0137] In some embodiments, the image reconstruction process may include a plurality of iterations. In each of the plurality of iterations, a PET image reconstructed in a prior iteration may be updated123 based on the objective function configured with the regularization parameter. In some embodiments, the boundary information of structures of the subject may be updated based on a reconstructed PET image in each iteration. In this case, the regularization parameter may also be updated in the plurality of iterations.
Conclusion
The prior art “nearest to the subject matter defined in the claims” (MPEP 707.05) made of record and not relied upon is considered pertinent to applicant's disclosure.
The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action:
Citation
Relevance
ZHANG et al. (US 2020/0342637 A1): same assignee
ZHANG teaches “an evaluation result” followed by an “determine…to update the…correction…to improve…the target PET image” via [0133][0134]:
[0133] The processing device 140A may determine whether a termination condition is satisfied in the current iteration. Exemplary termination conditions may include that a certain count of iterations is performed, the iteration operation lasts for more than a certain period, the first scatter correction sinogram has a desired image quality, etc. For example, the termination condition may be that more than a certain count of iterations is performed. The certain count may be a default value of the imaging system 100, or set by a user manually, or determined by the processing device 140A according to an actual need. The certain count may have any positive integer, for example, within a range from 2 to 20, or 3 to 8. For example, the certain count may be 4. In some embodiments, whether the termination condition is satisfied may be determined manually by a user. For example, the first scatter correction sinogram may be displayed on an interface implemented on, for example, the terminal 130, and the user may input an evaluation result regarding whether the first scatter correction sinogram has a desired image quality.
[0134] If it is determined that the termination condition is satisfied in the current iteration, the processing device 140A may designate the first scatter correction sinogram as the final scatter correction sinogram of the subject. If it is determined that the termination condition is not satisfied in the current iteration, the processing device 140A may proceed to a next iteration to update the first scatter correction sinogram until the termination condition is satisfied. By iteratively updating the first scatter correction sinogram, a final scatter correction sinogram having an improved accuracy may be generated so as to improve the accuracy of the target PET image to be reconstructed.
as the closest to the claimed: “in response to determining that at least one of the first evaluation result or the second evaluation result indicates that data correction needs to be performed, correcting the PET images” of claim 1.
LU et al. (WO 2023/131226 A1): same assignee
LU teaches “The correction module 222 may be further configured to judge whether the quality evaluation result meets a preset quality requirement. If not, the correction module 222 may correct the motion information and/or the list mode data according to a distribution of the position information to be evaluated within the preset sampling time period.” [0085] as shown in fig. 15:
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as the closest to the claimed: “in response to determining that at least one of the first evaluation result or the second evaluation result indicates that data correction needs to be performed, correcting the PET images” of claim 1.
KAPLAN et al. (CN 111867474 A) with SEARCH machine translation
KAPLAN teaches “CT image…evaluating…to correct the PET image”, pg. 13m 2nd txt blk:
Referring to FIG. 1, an illustrative imaging device 2 comprises a PET/CT imaging device, the PET/CT imaging device has a computer tomography (CT) frame 4 and a PET frame 6, a CT frame 4 comprises an X-ray tube and an X-ray detector array (not shown in the internal component) on the rotating machine frame. The PET frame 6 includes one or more PET detector rings (not shown internal components) for detecting gamma rays of 511keV. CT frame 4 and the PET frame 6 has a coaxial chamber for receiving the imaging object (e.g., medical patient), and the patient table or diagnosis table 8 is provided for loading the imaging object into the proper CT frame or PET frame. CT frame 4 is optional, but providing it is advantageous, because it can be used for collecting the CT image of the object, for evaluating the anatomical structure of the patient, locating for imaging organ or other internal features, generating the attenuation map for gamma ray absorption of 511keV to correct the PET image and so on.
as the closest to the claimed: “in response to determining that at least one of the first evaluation result or the second evaluation result indicates that data correction needs to be performed, correcting the PET images” of claim 1.
Bartelink et al. (Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict PET Image Quality of Three Generations EGFR TKI in Advanced-Stage NSCLC Patients)
Bartelink teaches a pharmacokinetic model is a “description124 of a physiological125 system… to represent various tissues”, pg. 4, 3rd para, 2nd S, predicting drug-tracer “B” in fig. 2:
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as the closest to the claimed “pharmacokinetic model” of claim 1.
Aarons (Editors’ view: Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed)
Aarons shows an example representation of the pharmacokinetic model and teaches/suggests that the compartments/boxes “should be viewed126 as” (pg. 1, rcol, 2nd para, last S) a mechanism127 or analogous thereto:
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as the closest to the claimed “pharmacokinetic model” of claim 1.
Burasothikul (Optimal dual-time-point dynamic 68Ga-PSMA-11 PET/CT protocols for parametric imaging generation in prostate cancer patients)
Burasothokul teaches generating parametric images based on the action of Tracer Kinetic Modeling:
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as the closest to the claimed “generating a preliminary PET parametric image by processing the PET images using at least one pharmacokinetic model” of claim 1.
Zuo et al. (Multiparametric Cardiac 18F-FDG PET in Humans: Kinetic Model Selection and Identifiability Analysis)
Zuo teaches kinetic modeling (inputting/outputting/processing) using an image function at frame-time t of the left ventricle represented in fig. 1 as C1(t):
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Piantadosi et al. (Comprehensive computer-aided diagnosis forbreast T1-weighted DCE-MRI through quantitative dynamical features and spatio-temporal local binary patterns)
Piantadosi teaches hand-crafted (deep learning) pharamacokinetic image feature extraction (i.e., outputting/processing features) representing characteristics by means of images according to pharacokinietic modeling (performing outputting/processing features) via page 1010, lcol, 3rd para:
Several literature proposals rely on hand-crafted features to extract the salience information from the images and push the task in a quantitative evaluation through classification models (either trained and non-trained). The features can be grouped according to the characteristics that they represent. Five major classes of features have been highlighted for detection or classification problems of neoplastic lesions by means of images: the dynamics features (DYN) quantify the temporal kinetic of the time intensity curve (TIC); the clinico-pathologic features (CLI) are directly extracted from the patient records and represent the clinical status and pathological condition of the patient; the textural features(TXT) are a set of measures designed to evaluate the perceived texture of an image on a global or local scale; the physiological-based pharmacokinetic features (PBPK) describe physiological parameters (absorption, distribution, metabolism, and excretion) of tissues, according to the PBPK modelling. Very few works make use of geometrical/morphological features (GEO) where the shape or the 3D surface of the lesion is used, mostly, to classify the lesions or to predict the recurrence of a primary tumour [72, 73].
as the closest to the claimed “pharmacokinetic model” of claim 1.
For all above references teaching pharmacokinetic model:
In view of all the above references teaching pharmacokinetic model/modeling, the art suggests that an image/data is input into the pharmacokinetic model such that a distinction between the image/data (being a representation) and the kinetic model (also being a representation) is not clear and thus is blurred. The distinction appears to be the output128/processing of the kinetic model as shown in Bartelink’s fig. 2: “B: Model 2” that predicts, given an input image/data or input tissue/tumor parameter, where tracer-drug “B” will be located in the model’s output image such as inside the “Lysosome”129 consuming “B”:
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THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS ROSARIO whose telephone number is (571)272-7397. The examiner can normally be reached Monday-Friday, 9AM-5PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at 571-272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DENNIS ROSARIO/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
1 scope: Linguistics, Logic. the range (i.e., every single word in claim 1 or the entire claim set) of words or elements of an expression (claim 1 or the entire claim set such as dependent claims) over which a modifier (a patent examiner) or operator (me) has control. (Dictionary.com)
2 evaluate VERB (USED WITH OBJECT: “the original PET images”): to determine or set the value or amount of; appraise. (Dictionary.com)
3 evaluation NOUN: an act or instance of evaluating or appraising. (Dictionary.com)
4 on: in connection, association, or cooperation with; as a part or element of. (Dictionary.com)
5 assess: to estimate or judge the value, character, etc., of; evaluate, wherein evaluate is defined: to judge or determine the significance, worth, or quality of; assess. (Dictionary.com)
6 evaluation NOUN: an act or instance of evaluating or appraising. (Dictionary.com)
7 on: in connection, association, or cooperation with; as a part or element of. (Dictionary.com)
8 evaluate: to judge or determine the significance, worth, or quality of; assess, wherein determine is defined: to conclude or ascertain, as after reasoning, observation, etc. (Dictionary.com)
9 determine: to conclude or ascertain, as after reasoning, observation, etc. (Dictionary.com)
10 colon: the sign (:) used to mark a major division in a sentence, to indicate that what follows is an elaboration, summation, implication, etc., of what precedes (“performing a quality evaluation on the PET images”); or to separate groups of numbers referring to different things, as hours from minutes in 5:30; or the members of a ratio or proportion, as in 1 : 2 = 3 : 6. (Dictionary.com)
11 evaluate: to determine or set the value or amount of; appraise, wherein determine is defined: to conclude or ascertain, as after reasoning, observation, etc. (Dictionary.com)
12determine: to conclude or ascertain, as after reasoning, observation, etc. (Dictionary.com)
13 MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses; and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose to the manipulative steps").
14 “the preliminary parametric image” is interpreted as –the preliminary PET parametric image”.
15 (italics) represent claim limitations already taught
16 The crossed text is a narrow subset of claim scope and thus does not limit the claim scope of claim 22.
17 MEANING AND PURPOSE I of claim 1 is “for quality evaluations of parametric imaging in position emission tomography (PET)”
18 BROAD LANGUAGE: -ing (of “comprising” or any –“ing” word in claims 1-20): a suffix of nouns formed from verbs, expressing the action of the verb or its result, product, material, etc. (the art of building; a new building; cotton wadding ), wherein etc is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted), wherein so is defined: likewise or correspondingly; also; too. (Dictionary.com)
19 BROAD CLAIM LANGUAGE: target: electronics an object to be detected by the reflection of a radar or sonar signal, etc, , wherein etc. is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted). (Dictionary.com)
20 to: (used for expressing aim, purpose, or intention), wherein aim is defined: the act of aiming or directing anything at or toward a particular point or target. (Dictionary.com)
21 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“difference time periods”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“difference time”), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
22 The claimed “difference time periods” is interpreted in the alternative as a coordinate-adjective Markush element: difference and time periods, i.e., “difference periods” OR “time periods”, wherein and is defined: A. (used to connect grammatically coordinate words, phrases, or clauses) along or together with; as well as; in addition to; besides; also; moreover. B. (used to connect alternatives). (Dictionary.com)
23 signal: Electronics. an electrical quantity or effect, as current, voltage, or electromagnetic waves, that can be varied in such a way as to convey information, wherein electromagnetic wave is defined: a wave produced by the acceleration of an electric charge and propagated by the periodic variation of intensities of, usually, perpendicular electric and magnetic fields, wherein periodic is defined: recurring at intervals of time, wherein interval is defined: an intervening period of time, wherein intervening is defined: to occur or happen between other events or periods, wherein other is defined: different or distinct from the one or ones already mentioned or implied. (Dictionary.com)
24 MEANING AND PURPOSE II of claim 1: “to generate a target PET parametric image”.
25 image: a physical likeness or representation of a person, animal, or thing, photographed, painted, sculptured, or otherwise made visible, wherein representation is defined: the act of portrayal, picturing, or other rendering in visible form, wherein portrayal is defined: the act of portraying, wherein portraying is defined: to make a likeness of by drawing, painting, carving, or the like, wherein drawing is defined: a sketch, plan, or design, especially one made with pen, pencil, or crayon, wherein plan is defined: a representation of a thing drawn on a plane, as a map or diagram. (Dictionary.com)
26 pharmacokinetic: a word derived from pharmacokinetics, wherein pharmacokinetics is defined: NOUN (used with a singular verb) the branch of pharmacology that studies the fate of pharmacological substances in the body, as their absorption, distribution, metabolism, and elimination, wherein pharmacological is defined: using, involving, or having to do with a drug or drugs. (Dictionary.com: AMERICAN)
27 Regarding the narrow subset of claim scope of the broadest reasonable claim construction of claim 1, see below prior art cited table’s last entry (at end of this Office action) about “pharmacokinetic model” being indistinguishable from an image, such as ZHENG’s fused image drug tracer camera map or claim 1’s “PET images” with understood tracer such as glucose or dopamine.
28 BROAD CLAIM LANGUAGE: model: a representation, usually on a smaller scale, of a device, structure, etc (Dictionary.com: BRITISH)
29 model: a simplified representation or description of a system or complex entity, esp one designed to facilitate calculations and predictions, wherein description is defined: the act, process, or technique of describing, wherein describe is defined: to draw a line or figure, such as a circle, wherein draw is defined: to depict or sketch (a form, figure, picture, etc) in lines, as with a pencil or pen, esp without the use of colour; delineate (Dictionary.com: BRITISH)
30 tracer: med any radioactive isotope introduced into the body to study metabolic processes, absorption, etc, by following its progress through the body with a gamma camera or other detector (Dictionary.com: BRITISH)
31 map: a maplike delineation, representation, or reflection of anything, wherein representation is defined: the state of being represented, where represent is defined: a picture, figure, statue, etc. , wherein figure is defined: form or shape, as determined by outlines or exterior surfaces, wherein shape is defined: something used to give form, as a mold or a pattern, wherein pattern is defined: a distinctive style, model, or form, wherein model is defined: a representation, generally in miniature, to show the construction or appearance of something, wherein representation is defined: a picture, figure, statue, etc., wherein picture is defined: any visible image, however produced. (Dictionary.com).
32 I am interpreting the claimed “model” and ZHENG’s “map” to mean the same thing (i.e., being an identity or an assertion that two terns, model & map, refer to the same thing): a delineation
33 MEANING AND PURPOSE III is claim 1’s “data correction needs to be performed”.
34 correct: Mathematics, Physics. to alter or adjust so as to bring into accordance with a standard or with a required condition, wherein required is defined: to have need of; need (Dictionary.com)
35 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“the PET images or [[a]] the preliminary PET parametric image”) that suggests (via “or” is alternative language) or makes a feature or step (in claim 1 last “wherein”: “wherein the preliminary PET parametric image is generated by processing the corrected PET images or the PET images using at least one pharmacokinetic model” or another step in claim 4) optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“the PET images or a preliminary PET parametric image”), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
36 The claim portions of Claims 1,3,4,7 in {{{triple curly brackets}}} is “a narrow subset of claim scope…that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation” via
MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
37 (italics) represent claim limitations already taught
38 (italics) represent claim limitations already taught
39 PET scanning: Computers, Medicine/Medical. the action or process of using a PET scanner to obtain an image, wherein PET scanner is defined: Computers, Medicine/Medical. a tomographic imaging device that yields visual information (aPET scan ) about the ongoing activity of the brain: positron-emitting isotopes, incorporated into biologically important compounds, are injected intravenously or administered by inhalation, and the resultant gamma radiation is sensed by detectors and converted into computer-generated images of blood flow, oxygen utilization, glucose uptake, etc.
40 signal-to-noise ratio: the ratio of one parameter, such as power of a wanted signal to the same parameter of the noise at a specified point in an electronic circuit, etc , wherein want is defined: to feel a need or a desire for; wish for. (Dictionary.com)
41 signal-to-noise ratio: the ratio of one parameter, such as power of a wanted signal to the same parameter of the noise at a specified point in an electronic circuit, etc , wherein want is defined: to feel a need or a desire for; wish for. (Dictionary.com)
42 Claims 1,3,4,7,6 in {{{triple curly brackets}}} is “a narrow subset of claim scope…that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation” via
MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
43 This “wherein” clause is not directed to MEANING AND PURPOSES I,II,III.
44 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation. (Dictionary.com)
45 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation. (Dictionary.com)
46 information: computing another word for data, wherein data is defined: a series of observations, measurements, or facts; information, wherein measurement is defined: an amount, extent, or size determined by measuring, wherein amount is defined: the full value, effect, or significance of something (Dictionary.com)
47 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“the corrected PET images or the PET images”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“the corrected PET images or the PET images”), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
48 Markush claim 7 is taught since the other Markush correcting alternative in claim 1 is already taught. Thus claim 7 does not limit the claim scope under the broadest reasonable interpretation of claims 1,4,7.
49 This “wherein” clause is not directed to MEANING AND PURPOSES I,II,III.
50 MPEP2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
51 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“the corrected PET images or the PET images” in claim 7) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“the corrected PET images or the PET images”), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
52 UNSATISFIED CONTINGENT LIMITATION (MPEP 2111.04 II. CONTINGENT LIMITATIONS): whether: if it is or was true that (Merriam-Webster.com)
53 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation. (Dictionary.com)
54 Claim portions of claims 5,7,8,9,10,11,12 in {{{triple curly brackets}}} is not “a limitation is a claim…wherein the clause gave ‘meaning and purpose to the manipulative steps’ “ via MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses; and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose to the manipulative steps").
55 This “wherein” clause is not directed to MEANING AND PURPOSES I,II,III.
56 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“a sample physical point in claim 9) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“ sample physical“ of “a sample physical point in claim 9), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
57 In view of MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss, the claimed “sample physical point” is interpreted in the alternative as a coordinate-adjective Markush element: sample and physical point, i.e., “sample point” OR “physical point”
58 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation, wherein element is defined: Geometry. one of the points, lines, planes, or other geometrical forms, of which a figure is composed. (Dictionary.com)
59 colon: the sign (:) used to mark a major division in a sentence, to indicate that what follows is an elaboration, summation, implication, etc., of what precedes, wherein what is defined: whatever; anything that, wherein anything is defined: any thing whatever; something, no matter what, wherein any is defined: one, a, an, or some; one or more without specification or identification. (Markush language) (Dictionary.com)
60 The claimed “sample PET images” is interpreted in the alternative as coordinate-adjective Markush alternatives: sample and PET images, i.e., “sample images” OR “PET images”.
61 PET scan: Computers, Medicine/Medical. A. an image obtained by positron emission tomography, using a PET scanner. B. an examination performed with a PET scanner. (Dictionary.com)
62 semicolon: the punctuation mark (;) used to indicate a major division in a sentence where a more distinct separation is felt between clauses or items on a list (Markush language) than is indicated by a comma, as between the two clauses of a compound sentence. (Dictionary.com)
63 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“a recommended pharmacokinetic model”) that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art.--.
64 The claimed “recommended pharmacokinetic model” is interpreted in the alternative as a coordinate-adjective Markush element: recommended and pharmacokinetic model, i.e., “recommended model” OR “pharmacokinetic model”.
65 BROAD CLAIM LANGUAGE: designating: to nominate or select for a duty, office, purpose, etc.; appoint; assign, wherein etc. is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted) (Dictionary.com)
66 information: Computers. A. important or useful facts obtained as output from a computer by means of processing input data with a program. Using the input data, we have come up with some significant new information. B. data at any stage of processing (input, output, storage, transmission, etc.).
67 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation. (Dictionary.com)
68 Due to the claim deletion (MEANING AND PURPOSES I,II, III.
69 PET: Computers, Medicine/Medical. positron emission tomography, wherein positron emission tomography is defined: the process of producing a PET scan.
70 raw: unprocessed or unevaluated. raw data. (Dictionary.com)
71 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 2nd para, 2nd & 3rd Ss:-- Language (“PET raw data”) that suggests (via “PET” modifying “raw” --defined Dictionary.com: raw: unprocessed or unevaluated--does not make grammatical sense; however, “PET”--defined via Dictioanry.com: positron emission tomography: the process of producing a PET scan”--modifying “data” as “PET data” makes grammatical sense: The process of producing a PET scan data) or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives (“PET raw” of “PET raw data”), the prior art teaches the element if one of the alternatives is taught by the prior art.--.
72 --raw PET data-- makes grammatical sense:--unprocessed or unevaluated process of producing a PET scan data--.
73 The claimed “recommended pharmacokinetic model” is interpreted in the alternative as a coordinate-adjective Markush element: recommended and pharmacokinetic model, i.e., “recommended model” OR “pharmacokinetic model”.
74 analog: of or relating to a mechanism, device, or technology that represents data by measurement of a continuous physical variable, as voltage or pressure, wherein physical is defined: of or relating to that which is material, wherein material is defined: anything that serves as crude or raw matter to be used or developed, wherein matter is defined: Something (positron or electron) that has mass. Most of the matter in the universe is composed of atoms which are themselves composed of subatomic particles. .(Dictionary.com)
75 “PET raw data” is interpreted the same as in claim 10.
76 The claimed “coincidence event” appears as a term of art.
77 “noise level” is interpreted as a cumulative adjective (noise-level)
78 BROAD CLAIM LANGUAGE: level: an extent, measure, or degree of intensity, achievement, etc..
79 signal-to-noise ratio: the ratio of one parameter, such as power of a wanted signal to the same parameter of the noise at a specified point in an electronic circuit, etc (Dictionary.com)
80 This “wherein” clause of claim 12 (a going-on-a-tangent claim) is not directed to MEANING AND PURPOSE I (evaluation), MEANING AND PURPOSE II (a target PET parametric image generation), MEANING AND PURPOSE III (evaluative image correction) of claim 1 and thus claim 12 is not a limitation.
81 MEANING AND PURPOSE I: “for quality evaluations of parametric imaging in positron emission tomography (PET)”
82 MEANING AND PURPOSE II: “to direct the system to perform operations including”
83 time: a particular period considered as distinct from other periods. (Dictionary.com)
84 MEANING AND PURPOSE III: “to generate a target PET parametric image”
85 voxel: Digital Technology. any one of the set of cubic elements that together make up a 3D graphic simulation or representation, wherein graphic is defined: giving a clear and effective picture; vivid, wherein vivid is defined: strikingly bright or intense, as color, light, etc., wherein color is defined: the quality of an object or substance with respect to light reflected by the object, usually determined visually by measurement of hue, saturation, and brightness of the reflected light; saturation or chroma; hue, wherein measurement is defined: extent, size, etc., ascertained by measuring, wherein measuring is defined: to estimate the relative amount, value, etc., of, by comparison with some standard. . . (Dictionary.com)
86 the: (used, especially before a noun, with a specifying or particularizing effect, as opposed to the indefinite or generalizing force of the indefinite article a or an ). (Dictionary.com)
87 pixel: The most basic unit of an image displayed on a computer or television screen or on a printer. Pixels are generally arranged in rows and columns; a given combination among the pixels of various brightness and color values (claim 14’s “pixel values”) forms an image, wherein given is defined: stated, fixed, or specified. (Dictionary.com)
88 MEANING AND PURPOSE IV: “the corresponding pixel…needs to be corrected”.
89 and: (used to connect alternatives). (Dictionary.com)
90 correct: Mathematics, Physics. to alter or adjust so as to bring into accordance with a standard or with a required condition, wherein required is defined: to have need of; need (Dictionary.com)
91 Due to the deletion ( MEANING AND PURPOSES I,II,III,IV of claim 14.
92 evaluation: an act or instance of evaluating or appraising, wherein evaluate is defined:
to determine or set the value or amount of; appraise. (Dictionary.com)
93 This deleted portion of claim 19 is directed to MEANING AND PURPOSE IV (like claim 1’s “data correction needs to be performed”) of claim 14.
94 determine: to conclude or ascertain, as after reasoning, observation, etc., wherein ascertain is defined: to find out definitely; learn with certainty or assurance; determine. (Dictionary.com)
95 This “wherein” clause of claim 21 is not directed to MEANING AND PURPOSES I,II,III,IV of claim 14.
96 This crossed-out “wherein” clause in {{{triple-curly brackets}}} is not directed to MEANING AND PURPOSES I,II,III,IV of claim 14 and thus is not a claim limitation.
97 This crossed-out “wherein” clause in {{{triple-curly brackets}}} is not directed to MEANING AND PURPOSES I,II,III,IV of claim 14 and thus is not a claim limitation.
98 kinetic: pertaining to motion. (Dictionary.com)
99 real-time: Computers. of or relating to applications in which the computer must respond as rapidly as required by the user or necessitated by the process being controlled. (Dictionary.com)
100 Applicant’s Disclosure:
[0018] According to yet another aspect of the present disclosure, a non-transitory computer readable medium may be provided. The non-transitory computer readable medium may include at least one set of instructions for parametric imaging in PET. When executed by one or more processors of a computing device, the at least one set of instructions may cause the computing device to perform a method. The method may include obtaining multiple PET images collected via a PET scan of a target subject. The PET images may be dynamic PET images for difference time periods during the PET scan and used to generate a target PET parametric image of the target subject. The method may also include determining whether data correction needs to be performed in a process of generating the target PET parametric image. The method may further include, in response to determining that data correction needs to be performed, correcting the PET images or a preliminary PET parametric image, and generating the target PET parametric image of the target subject based on the corrected PET images or the corrected preliminary PET parametric image, wherein the preliminary PET parametric image is generated by processing the PET images using at least one pharmacokinetic model.
[
0036] Generally, the word “module,” “unit,” or “block,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions. A module, a unit, or a block described herein may be implemented as software and/or hardware and may be stored in any type of non-transitory computer-readable medium or another storage device. In some embodiments, a software module/unit/block may be compiled and linked into an executable program. It will be appreciated that software modules can be callable from other modules/units/blocks or from themselves, and/or may be invoked in response to detected events or interrupts. Software modules/units/blocks configured for execution on computing devices may be provided on a computer-readable medium, such as a compact disc, a digital video disc, a flash drive, a magnetic disc, or any other tangible medium, or as a digital download (and can be originally stored in a compressed or installable format that needs installation, decompression, or decryption prior to execution). Such software code may be stored, partially or fully, on a storage device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules/units/blocks may be included in connected logic components, such as gates and flip-flops, and/or can be included of programmable units, such as programmable gate arrays or processors. The modules/units/blocks or computing device functionality described herein may be implemented as software modules/units/blocks, but may be represented in hardware or firmware. In general, the modules/units/blocks described herein refer to logical modules/units/blocks that may be combined with other modules/units/blocks or divided into sub-modules/sub-units/sub-blocks despite their physical organization or storage. The description may be applicable to a system, an engine, or a portion thereof.
101 MEANING AND PURPOSE I: “for quality evaluations of parametric imaging in positron emission tomography (PET)”
102 MEANING AND PURPOSE II: “causes the computing device to perform a method”
103 MEANING AND PURPOSE III: “to generate a target PET parametric image”
104 kinetic: pertaining to motion (Dictionary.com)
105 algorithm: Computers. an ordered set of instructions recursively applied to transform data input into processed data output, such as a mathematical solution, search engine result, descriptive statistics, or predictive text suggestions, wherein output is defined: Computers. information in a form suitable for transmission from internal to external units of a computer, or to an outside medium. (Dictionary.com)
106 MEANING AND PURPOSE IV: “determining that motion correction is needed”
107 This “wherein” clause is directed to claim 20’s random/tangential “correcting the PET images” and not directed to MEANING AND PURPOSE IV. Thus this “wherein” clause in {{{triple-brackets}}} is not a limitation in a claim.
108 This “wherein” clause is directed to MEANING AND PURPOSE I of claim 1 “for quality evaluations of parametric imaging in position emission tomography (PET)”
109 include: to contain, as a whole does parts or any part or element, wherein contain is defined: to be equal to. (Dictionary.com)
110 between: linking; connecting. (Dictionary.com)
111 Limitations in {italics) are already taught
112 Limitations in {italics) are already taught
113 BROAD CLAIM LANGUAGE: threshold: a level or point at which something would happen, would cease to happen, or would take effect, become true, etc (Dictionary.com)
114 assess: to estimate or judge the value, character, etc., of; evaluate., wherein value is defined: Mathematics. a point in the range of a function; a point in the range corresponding to a given point in the domain of a function. The value of x2 at 2 is 4. (Dictionary.com)
115 This “wherein” clause if giving MEANING AND PURPOSE to claim 14’s “correcting…the preliminary PET parametric image” of claim 14; thus, claim 22 is a claim limitation.
116 the: (used, especially before a noun, with a specifying or particularizing effect (i.e. referring to claim 14’s “pixel values”), as opposed to the indefinite or generalizing force of the indefinite article a or an ). (Dictionary.com)
117 pixel: The most basic unit of an image displayed on a computer or television screen or on a printer. Pixels are generally arranged in rows and columns; a given combination among the pixels of various brightness and color values (claim 14’s “pixel values”) forms an image, wherein given is defined: stated, fixed, or specified. (Dictionary.com)
118 The portion in {{{triple-curly brackets}}} of the “wherein” clause is not directed to MEANING AND PURPOSES I,II,III,IV of claim 14.
119 (italics) represent claim limitations already taught
120 “the preliminary parametric image” is interpreted as –the preliminary PET parametric image”.
121 (italics) represent claim limitations already taught
122 The crossed text is a narrow subset of claim scope and thus does not limit the claim scope of claim 22.
123 update: Computers. to incorporate new or more accurate information in (a database, program, procedure, etc.). (Dictionary.com)
124 description: a statement, picture in words, or account that describes; descriptive representation, wherein describe is defined: to represent or delineate by a picture or figure. (Dictionary.com)
125 physiological: of or relating to physiology, wherein physiology is defined: the organic processes or functions in an organism or in any of its parts. (Dictionary.com)
126 view: an instance of seeing or beholding; visual inspection. (Dictionary.com)
127 BROAD LANGUAGE: mechanism: the structure or arrangement of parts of a machine or similar device, or of anything analogous, wherein analogous is defined: having analogy; corresponding in some particular. A brain and a computer are analogous. (Dictionary.com)
128 “output” and “input”: applicant’s disclosure:
[0163] In some embodiments, the processing device 140 may determine a first TAC of the physical point based on pixel values corresponding to the physical point in the PET images. The first TAC of the physical point may be a measurement TAC. More descriptions of the generation manner of the measurement TAC can be found in descriptions of operation 710. Further, the processing device 140 may determine a second TAC of the physical point based on the pixel values corresponding to the physical point in the PET images and the pharmacokinetic model corresponding to the physical point. The second TAC may be a fitting TAC determined by the pharmacokinetic model. Specifically, the processing device 140 may input the pixel values corresponding to the physical point in the PET images into the pharmacokinetic model, and the pharmacokinetic model may output the second TAC.
129 lysosome: A cell organelle that is surrounded by a membrane, has an acidic interior, and contains hydrolytic enzymes that break down food molecules, especially proteins and other complex molecules. Lysosomes fuse with vacuoles to digest their contents. The digested material is then transported across the organelle's membrane for use in or transport out of the cell. (Dictionary.com)
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