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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 13-19, and 22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without integration into a practical application or recitation of significantly more.
In the analysis below, the method of independent claim 18 is considered representative of independent claims 1, 18, and 22 since all of the independent claims recite identical steps despite being directed to different statutory matter. Furthermore, each of independent claims 1, 18, and 22 are directed to one of the four statutory categories of eligible subject matter; thus, the claims pass Step 1 of the Subject Matter Eligibility Test (See flowchart in MPEP 2106).
Step 2A, prong 1: Yes
The independent claims are directed to
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When viewed under the broadest most reasonable interpretation, the instant claims are directed to Judicial Exception – an abstract idea belong to the group of mental process. Particularly, step 3 can be performed mentally. For example, a trained radiologist could determine based on their mind and expertise boundary information relating to a target volume from a received patient scan, the use of a machine learning technique here in the claim language is a generic form of learning from an image and no specifics are given as to how the machine learning is used.
Reference may be made to the July 2024 PEG and those various limitations drawn to the mental processes grouping(s), to include those of Example 47 claim 2. The claims/limitations in question are recited at a high level of generality and lack any specifics precluding such ‘performing’, ‘determining’, ‘implementing’, ‘executing’, etc., from being interpreted under the mental processes grouping practically performed in the mind. As identified in the most recent PEG, even a form of automating that broadly/generically involves the use of a machine learning model, would fail to preclude the limitations in question from being drawn to the mental processes grouping (see guidance with respect to ‘apply it’ consideration of MPEP 2106.05(f)). Hence, the limitation 3 is interpreted as a mental step. Dependent claims similarly analyzed, further limit said ‘executing’ second action, but not in such a manner so as to preclude an interpretation directed to the identified exception.
Additional elements
The additional elements recited in each of the independent claims are a 1 and 2 obtaining one or more target images of a subject and obtaining a target volume segmentation model having been trained according to a machine learning technique.
Step 2A, prong 2: No
The above-identified additional elements do not integrate the judicial exception into a practical application.
The steps of 1 and 2 amount to data gathering which is insignificant pre-solution activity which does not integrate the claimed mental process into a practical application (See MPEP 2106.05(g)).
The machine learning technique amounts to merely using a generic computer as a tool to perform the claimed mental process. Implementing an abstract idea on a computer does not integrate a judicial exception into a practical application (See MPEP 2106.05(f)).
Moreover, the additional elements of the claims do not recite an improvement in the functioning of a computer or other technology or technical field, the claimed steps are not performed using a particular machine, the claimed steps do not effect a transformation, and the claims do not apply the judicial exception in any meaningful way beyond generically linking the use of the judicial exception to a particular technological environment (See MPEP 2106.04(d)). Therefore, the analysis under prong two of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Step 2B: No
The pending claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As explained above in Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer. Each of the additional elements are generic computer features which perform generic computer functions that are well-understood, routine, and conventional and do not amount to more than implementing the abstract idea with a computerized system.
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation, and mere implementation on a generic computer does not add significantly more to the claims. Accordingly, the analysis under step 2B of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Claims 2-6, 13-17 are further drawn to details that a human could carry out in their mind .
Claim Rejections - 35 USC § 102
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.
Claims 1-2, 13, 18-19, and 22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lou et al. US 2020/0069973 (hereinafter “Lou”).
Regarding claim 1, Lou discloses a system for clinical target contouring in radiotherapy (see paragraph 0007, systems for providing decision support in a medical therapy including segmentation, see figure 6)
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, comprising: at least one storage device including a set of instructions; and at least one processor configured to communicate 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 (see above paragraph 0007 instructions on computer readable media) including: obtaining one or more target images of a subject, the subject including a target region to which a radiation treatment is directed (see paragraph 0099, automated target structure contouring is provided for radiotherapy planning, the input of the network isa computed tomography image that includes gross tumor volume)
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; obtaining a target volume segmentation model having been trained according to a machine learning technique (see above paragraph 0099 where a trained segmentation model is used to generate the segmentation); and determining, based on the one or more target images and the target volume segmentation model, boundary information relating to a target volume of the subject, the target volume including at least part of the target region (see above paragraph 0099 and figure 6 where a masked volume is output 66 which is the boundary information relating to the target volume of the subject, see paragraph 0085).
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Regarding claim 2, Lou discloses wherein the target volume includes at least one of a gross tumor volume (GTV), a clinical target volume (CTV), or a planning target volume (PTV) of the subject (see paragraph 0099, GTV).
Regarding claim 13, Lou discloses generating, based on the boundary information relating to the target volume of the subject, a treatment plan directed to the target region (see paragraph 0095)
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Claims 18-19 are similarly analyzed to claims 1-2.
Claim 22 is similarly analyzed to claim 1.
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.
Claims 3-6, and 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Lou in view of Hibbard US 2019/0333623.
Regarding claim 3, Lou discloses wherein the target volume segmentation model has been trained according to a loss function the loss function being constructed according to a contouring guideline for delineating the target region (see paragraph 0085 above, for training the segmentation may be compared to ground truth segmentation to find the loss).
Lou does not explicitly disclose delineating one or more organs at risk (OARs) near the target region.
It is well known to delineate the organs at risk surrounding a tumor as shown by Hibbard who teaches to delineate the organs at risk (see paragraph 0057).
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Lou and Hibbard are analogous art because they are from the same field of endeavor of segmentation of medical image.
Before the effective filing date of the invention it would have been obvious to combine Lou and Hibbard to delineate the organs at risk surrounding the tumor as well as the tumor. The motivation for doing so would be to study the dose distribution not only in the target but also in the organs at risk.
Regarding claim 4, similar to claim 3, Lou teaches a target model segmentation for a clinical target volume with a loss function (see above paragraph 0099) and Hibbard teaches that this can be done for organs at risk as well (see paragraph 0057).
Regarding claim 5 Lou discloses determining position information of the boundary information (see paragraph 0083, segmenting involves labeling by location).
Regarding claim 6, Lou discloses that the locations of the image may be in a Cartesian coordinate system (see paragraph 0068).
Regarding claim 14, Lou discloses determining, based on the one or more target images, a model input of the target volume segmentation model; obtaining a model output of the target volume segmentation model by inputting the model input into the target volume segmentation model; and determining, based on the model output, the boundary information relating to the target volume, wherein the model output includes the boundary information relating to the target volume and boundary information
Lou does not explicitly disclose that the boundary information is related to the OARs near the target region, however as discussed above Hibbard discloses this in paragraph 0057.
Before the effective filing date of the invention it would have been obvious to combine Lou and Hibbard to delineate the organs at risk surrounding the tumor as well as the tumor. The motivation for doing so would be to study the dose distribution not only in the target but also in the organs at risk.
Regarding claim 15, Hibbard discloses obtaining boundary information relating to one or more OARs near the target region; and determining the boundary information relating to the target volume based on the one or more target images, the target volume segmentation model, and the boundary information relating to the one or more OARs (see above paragraph 0057).
Regarding claim 16, Hibbard discloses obtaining one or more OAR segmentation models; and determining, based on the one or more target images and the one or more OAR segmentation models, the boundary information relating to the one or more OARs near the target region (see paragraph 0057 copied above).
Regarding claim 17, Lou discloses determining, based on the one or more target images and the boundary information relating to the one or more OARs, a stage of the target region (see paragraph 0130, the stages of tumor progression are determined)
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; and determining the boundary information relating to the target volume based on the one or more target images, the target volume segmentation model, the boundary information relating to the one or more OARs, and the stage of the target region (see figure 6 of Lou and paragraph 0057 of Hibbard).
Allowable Subject Matter
Claims 7-12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see the attached 892 notice of references cited.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN B STREGE whose telephone number is (571)272-7457. The examiner can normally be reached M-F 9-5 (PST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chan Park can be reached at (571)272-7409. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOHN B STREGE/Primary Examiner, Art Unit 2669
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