Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Typographic Conventions
Throughout this office action, shorthand notation for referencing locations of elements in documents are utilized. The following is a brief summary of the shorthand utilized:
Sec. – is used to denote an associated section with a header in non-patent literature
¶ – is used to denote the number and location of a paragraph
col. – is used to denote a column number
ln. – is used to denote a line; if a line number is not demarcated in a document, the line number will be assumed to start at 1 for each paragraph.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Acknowledgement is made of applicant’s claim for foreign priority based on application JP 2023-051230 filed on 03/28/2023 under 35 U.S.C. 119(a)-(d).
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/06/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. The present invention relates to determining the position of an indirect finding associated with the occurrence of a lesion and generating medical images of said indirect finding. Adding sufficient detail to the title relating to the field of endeavor in medical image analysis would properly reflect the purpose or context of the present invention.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-6 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 5 & 6 recite the limitation “a medical image” in two distinctly separate contexts (reproduced from claim 1 below):
where the image processing apparatus determines a position of an indirect finding associated with the occurrence of a lesion in a medical image [ln. 4-5].
where the image processing apparatus generates a medical image in which the indirect finding is generated at the determined position [ln. 6-7].
It is unclear from the claim language that these are two distinctly different medical images which renders the claims indefinite. Further clarification, such as distinguishing these two medical images as “a first medical image” or “a second medical image” is needed. Therefore, the applicant has failed to particularly point out and distinctly claim the subject matter that the inventor regards as the invention.
Claim 2 is dependent on claim 1, and is therefore rejected for its dependence on an indefinite claim.
Claims 3 & 4 are dependent on claim 1, and are therefore rejected on their dependence on an indefinite claim. Claims 3 & 4 also recite the limitation “the medical image”. It is unclear if this is intended to be distinct from the “a medical image” recited in claim 1. Further clarification is needed.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1,2 & 4-6 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Osawa, Akira (US 2019/0131012 A1).
Regarding claim 1, Osawa disclose an image processing apparatus (image search device 1 [¶0041; Fig. 2]) comprising:
at least one processor (central processing unit (CPU) 11 [¶0045; Fig. 2]),
wherein the processor
determines a position of an indirect finding associated with occurrence of a lesion in a medical image (here an indirect finding is interpreted as a secondary pathology indicating the presence or future occurrence of a lesion; key finding specification unit 25 specifies a position of a key finding in examination image V0 [¶0082; Fig. 12], with examples of key findings outlined in Fig. 5 (see row 6 relating key findings indicating pulmonary lesions)) based on input information including a position of the lesion (a voxel region of a three-dimensional image having a known lesion is used as teacher data for the input layer 41 of the multilayer neural network 40 [¶0053-54; Fig. 3]), and
generates a medical image in which the indirect finding is generated at the determined position in a normal medical image in which the lesion has not occurred or (due to the use of the disjunctive “or” in the claim language, limitations with respect to “in a normal medical image in which the lesion has not occurred” are not being mapped to this reference [see MPEP § 2173.05(h)]) in an abnormal medical image in which the lesion has occurred (a labeled examination image V1 is generated based on the finding classification results of the examination image V0 [¶0064; Figs. 4 & 6]).
Regarding claim 2, Osawa teaches the image processing apparatus according to claim 1 (as previously described),
wherein the input information including the position of the lesion is a position of the lesion in the abnormal image (a voxel region of a three-dimensional image having a known lesion is used as teacher data for the input layer 41 of the multilayer neural network 40 [¶0053-54; Fig. 3]).
Regarding claim 4, Osawa teaches the image processing apparatus according to claim 1 (as previously described),
wherein the input information including the position of the lesion is data in which a value indicating existence of the lesion is defined in a region in which the lesion exists in the medical image (a voxel region of a three-dimensional image having a known lesion is used as teacher data for the input layer 41 of the multilayer neural network 40 [¶0053-54; Fig. 3]).
Regarding claim 5, Osawa teaches an image processing method (flowchart of image processing method [Fig. 12]) executed by a processor (central processing unit (CPU) 11 [¶0045; Fig. 2]) of an image processing apparatus (image search device 1 [¶0041; Fig. 2]), the method comprising:
determining a position of an indirect finding associated with occurrence of a lesion in a medical image (here an indirect finding is interpreted as a secondary pathology indicating the presence or future occurrence of a lesion; key finding specification unit 25 specifies a position of a key finding in examination image V0 [¶0082; ST5 of Fig. 12], with examples of key findings outlined in Fig. 5 (see row 6 relating key findings indicating pulmonary lesions)) based on input information including a position of the lesion (a voxel region of a three-dimensional image having a known lesion is used as teacher data for the input layer 41 of the multilayer neural network 40 [¶0053-54; Fig. 3]); and
generating a medical image in which the indirect finding is generated at the determined position in a normal medical image in which the lesion has not occurred or (due to the use of the disjunctive “or” in the claim language, limitations with respect to “in a normal medical image in which the lesion has not occurred” are not being mapped to this reference [see MPEP § 2173.05(h)]) in an abnormal medical image in which the lesion has occurred (a labeled examination image V1 is generated based on the finding classification results of the examination image V0 [¶0064; Figs. 4 & 6]).
Regarding claim 6, Osawa teaches a non-transitory computer-readable storage medium (memory 12 and storage 13 [¶0045; Fig. 2]) storing an image processing program (flowchart of image processing method [Fig. 12]) for causing a processor (central processing unit (CPU) 11 [¶0045; Fig. 2]) of an image processing apparatus (image search device 1 [¶0041; Fig. 2]) to execute:
determining a position of an indirect finding associated with occurrence of a lesion in a medical image (here an indirect finding is interpreted as a secondary pathology indicating the presence or future occurrence of a lesion; key finding specification unit 25 specifies a position of a key finding in examination image V0 [¶0082; ST5 of Fig. 12], with examples of key findings outlined in Fig. 5 (see row 6 relating key findings indicating pulmonary lesions)) based on input information including a position of the lesion (a voxel region of a three-dimensional image having a known lesion is used as teacher data for the input layer 41 of the multilayer neural network 40 [¶0053-54; Fig. 3]); and
generating a medical image in which the indirect finding is generated at the determined position in a normal medical image in which the lesion has not occurred or (due to the use of the disjunctive “or” in the claim language, limitations with respect to “in a normal medical image in which the lesion has not occurred” are not being mapped to this reference [see MPEP § 2173.05(h)]) in an abnormal medical image in which the lesion has occurred (a labeled examination image V1 is generated based on the finding classification results of the examination image V0 [¶0064; Figs. 4 & 6]).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Osawa, Akira (US 2019/0131012 A1) further in view of Muller et al (US 2023/0041804 A1).
Regarding claim 3, Osawa teaches the image processing apparatus according to claim 1 (as previously described), but does not teach input information including a probability map for the occurrence of a lesion.
Muller et al, however, is analogous art pertinent to the technological field of the present application and discloses input information including a spatial probability map indicating the probability for the occurrence of a lesion. More specifically, Muller et al teach wherein the input information including the position of the lesion is a probability map in which a probability of occurrence of the lesion is defined for each position in the medical image (trained Machine Learning Classifier infers where lesions may appear and generates a probability map of where lesions may appear in the future [¶0039; Fig. 12]). Osawa already teaches using input information indicating the position of a known lesion in a medical image to train a neural network to generate a medical image of the indirect finding at a position of the lesion. The use of spatial probability maps to indicate the likelihood and position of an occurrence of a given pathology as a training input for a machine learning model is well-known in the art, as taught by Muller. Therefore, the substituted components and their functions are known in the art. Furthermore, one of ordinary skill in the art could have easily substituted the spatial probability map for the location information in Osawa, as they both teach knowing a general location of a lesion; Furthermore, the results of the substitution would have been predictable -- simple substitution of one known form of input representation for another achieves the same purpose: providing spatial information to inform a neural network of the location of a lesion.
Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the present application to utilize the probability map presented by Muller at al as input information for the image processing device disclosed by Osawa to more readily detect indirect findings associated with the occurrence of lesion.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Yoo et al (US 2022/0261988 A1) disclose a method for detecting abnormal regions of interest in pathological slide images using a machine learning model.
Guendel et al (US 2021/0287799 A1) disclose a method for generating modified medical image for displaying an abnormal structure from a patient image.
Lee et al (US 2020/0226752 A1) disclose an apparatus for acquiring a normal and abnormal medical image and generating a virtual lesion image.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael M. Sofroniou whose telephone number is (571)-272-0287. The examiner can normally be reached M-F: 8:0 AM - 5:00 PM.
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, John M. Villecco can be reached at (571) 272-7319. 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.
/MICHAEL M SOFRONIOU/Examiner, Art Unit 2661
/JOHN VILLECCO/Supervisory Patent Examiner, Art Unit 2661