DETAILED ACTION
Claims 1-13 are currently pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/29/2024 and 11/13/2024 have been considered by the Examiner.
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, 7-10, and 12-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhou (US 2019/0205606).
Regarding claim 1, Zhou teaches:
An image processing device comprising:
at least one memory configured to store instructions: (Zhou, [0036] processor with memory) and
at least one processor configured to execute the instructions to:(Zhou, [0036] processor with memory)
an acquisition means configured to acquire time series images obtained by photographing an examination target by using an endoscope; (Zhou [0003] endoscopic imaging)
generate a plurality of mask images, which indicate candidate regions for an attention part with different levels of granularity, for each of the time series images; (Zhou [009] At step 910, Gaussian probability maps at multiple different scales are generated from the received medical image using the trained DI2IN )and
select an output image for output use from the time series images, based on the plurality of mask images. (Zhou [0094] At step 912, the Gaussian probability maps generated at the multiple scales from the received medical image are combined into a combine probability map…At step 914 the target landmark is detected or the boundary of the target anatomical object is segmented in the received medical image based on the combined probability map)
Regarding claim 7, Zhou teaches:
The image processing device according to claim 1,output control means configured wherein the at least one processor is configured to further execute the instructions to output information regarding the output image. (Zhou [0095] The detected landmark is then output, for example, by displaying the detected landmark or segmented boundary on a display device of a computer system)
Regarding claim 8, Zhou teaches:
The image processing device according to claim 7 wherein the at least one processor is configured to execute the instructions to display the output image or an image based on the output image on a display device. (Zhou [0095] The detected landmark is then output, for example, by displaying the detected landmark or segmented boundary on a display device of a computer system)
Regarding claim 9, Zhou teaches:
The image processing device according to claim 7,
wherein the at least one processor is configured to execute the instructions to input the output image to a segmentation model and display, on a display device, information outputted by the segmentation model accordingly, wherein the segmentation model is a model configured to output, when an image is inputted thereto, information regarding a candidate region for an attention part in the inputted image. (Zhou [0094] At step 912, the Gaussian probability maps generated at the multiple scales from the received medical image are combined into a combine probability map…At step 914 the target landmark is detected or the boundary of the target anatomical object is segmented in the received medical image based on the combined probability ma. [0095] The detected landmark is then output, for example, by displaying the detected landmark or segmented boundary on a display device of a computer system))
Regarding claim 10, Zhou teaches:
The image processing device according to claim 7, wherein the output at least one processor is configured to execute the instructions to display, on a display device, an image indicating a candidate area for the attention part based on the mask images associated with the output image. (Zhou [0095] The detected landmark is then output, for example, by displaying the detected landmark or segmented boundary on a display device of a computer system)
Regarding claim 12, Zhou teaches:
An image processing method executed by a computer, the image processing method comprising:
acquiring time series images obtained by photographing an examination target by using an endoscope; (Zhou [0003] endoscopic imaging)
generating a plurality of mask images, which indicate candidate regions for an attention part with different levels of granularity, for each of the time series images; (Zhou [009] At step 910, Gaussian probability maps at multiple different scales are generated from the received medical image using the trained DI2IN ) and
selecting an output image for output use from the time series images, based on the plurality of mask images. (Zhou [0094] At step 912, the Gaussian probability maps generated at the multiple scales from the received medical image are combined into a combine probability map…At step 914 the target landmark is detected or the boundary of the target anatomical object is segmented in the received medical image based on the combined probability map)
Regarding claim 13, Zhou teaches:
A non-transitory computer readable storage medium storing a program executed by a computer, the program causing the computer to: (Zhou, [0036] processor with memory)
acquire time series images obtained by photographing an examination target by using an endoscope; (Zhou [0003] endoscopic imaging)
generate a plurality of mask images, which indicate candidate regions for an attention part with different levels of granularity, for each of the time series images; (Zhou [009] At step 910, Gaussian probability maps at multiple different scales are generated from the received medical image using the trained DI2IN )and
select an output image for output use from the time series images, based on the plurality of mask images. (Zhou [0094] At step 912, the Gaussian probability maps generated at the multiple scales from the received medical image are combined into a combine probability map…At step 914 the target landmark is detected or the boundary of the target anatomical object is segmented in the received medical image based on the combined probability map)
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Zhou as applied to claim 1 above, and further in view of Sung (US 2020/0278408).
Regarding claim 11, Zhou fails to teach:
The image processing device according to claim 1, wherein the attention part is a part for a biopsy.
Sung teaches:
The image processing device according to claim 1, wherein the attention part is a part for a biopsy. (Sung [0036] hierarchical coarse-to-fine CNNs to segment voxel-level breast cancer tumor masks from the dynamic contrast enhanced (DCE)-MRI data and suggest biopsy locations).
Before the time of filing, it would have been obvious to one of ordinary skill in the art to identify biopsy locations (as taught by Sung) with the hierarchical segmentation method of Zhou. The inventions lie in the same field of endeavor of medical image analysis. The motivation to combine the references is to improve cancer diagnosis. See Sung [0003].
Allowable Subject Matter
Claims 2-6 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.
Regarding claim 2, neither the closest known prior art, nor any reasonable combination thereof, teaches:
The image processing device according claim 1 wherein the at least one processor is configured to execute the instructions to make a similarity determination among the plurality of mask images, for each of the time series images and select the output image based on a result of the similarity determination.
Claims 3-6 depend from claim 2 and are therefore also objected to as being dependent upon a rejected base claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Refer to PTO-892, Notice of References Cited for a listing of analogous art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Molly K Wilburn whose telephone number is (571)272-3589. The examiner can normally be reached Monday-Friday 8am-4pm.
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/Molly Wilburn/Primary Examiner, Art Unit 2666