DETAILED ACTION
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 § 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.
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(s) 1-2 and 6-10 is/are rejected under 35 U.S.C. 102(a)(1) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over Sharma et al. (US 2019/0326007) hereinafter known as Sharma.
With regards to claim 1 and 9-10, Sharma discloses a medical image diagnosis apparatus (FIG. 2; [0014]; System for imaging a patient and generating of a radiology report)[0001][0002] and method [0003], comprising:
a medical scanner configured to perform a scan on a subject to obtain an image ([0003][0063]; “…a medical imaging scanner scans a patient. The medical imaging scanner is any medical imager, such as a CT, MR, nuclear medicine, or ultrasound scanner.”) processing circuitry [0026][0038] configured to:
acquire subject information regarding the subject that includes a first medical image obtained by capturing an image of a diagnosis target region of the subject ([0059]; “… A medical imager scans in act 40…”) ([0083]; “…a first scan is of a liver,…”) under a first image capturing condition ([0021][0022][0069]; “The scan data, patient information, and/or scan settings may be also received.”),
determine a second image capturing condition to capture a second medical image of the subject ([0036]“The processor 24 outputs feedback in the form of settings for scan or image processing parameters to the medical imager 22. The settings are to redo a scan…and/or to perform a different scan.”) based on the subject information and a learned model obtained by executing learning while associating evaluation information regarding a medical image and an image capturing condition [0036][0040],
control the medical scanner to perform the scan on the subject by using the medical scanner with the determined second image capturing condition ([0036]; “Based on the clinical finding, a further scan using … different settings to focus on a vessel or pathology is to be performed… the feedback is a request to perform a further scan or change some aspect of the scanning.”) and
obtain a medical image of the subject from the medical scanner [0036][0059][0082].
With regards to claim 2, Sharma discloses the medical image diagnosis apparatus according to claim 1, wherein the second image capturing condition includes information regarding execution or non- execution of next image capturing [0060], and an image capturing position of the subject in a case where the next image capturing is to be executed ([0021] teaches of spatial position as a scan parameter.).
With regards to claim 6, Sharma discloses the medical image diagnosis apparatus according to claim 1, further comprising:
an X-ray generation unit configured to generate an X-ray [0019]; and
an X-ray detector configured to detect the X-ray [0019][0064],
wherein the first image capturing condition and the second image capturing condition include an image capturing position to which the X-ray is emitted ([0064] in view of the rejection of claim 1), and
wherein an image capturing position included in the second image capturing condition is within an unimaged portion of the diagnosis target region that excludes an image capturing position of the first medical image [0083].
With regards to claim 7, Sharma discloses the medical image diagnosis apparatus according to claim 1,
wherein the first medical image and the second medical image are magnetic resonance images [0019], and
wherein the first image capturing condition and the second image capturing condition include an image capturing position and a type of an image in magnetic resonance imaging [0019] ([0021]; spatial position)
With regards to claim 8, Sharma discloses the medical image diagnosis apparatus according to claim 1, further comprising an ultrasonic probe configured to transmit an ultrasonic wave to the subject,
wherein the first image capturing condition and the second image capturing condition include information regarding a position and an angle of the ultrasonic probe. [0019][0031][0063]
Claim(s) 3-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sharma, and further in view of Gheorghita et al. (US 2022/0093270) hereinafter known as Gheorghita.
With regards to claim 3, Sharma teaches of scanning for a particular disease [0022]. Sharma further teaches of a processor configured to determine clinical findings wherein the findings provide a severity, location, relationship to a symptom, and/or type of pathology or disease [0034]. Also, the reference teaches that the image processor reconstructs using estimate scalar values for the different locations in the patient from the scan data [0076]. Further, the reference teaches that the image processor uses clinical identification to select image processing wherein the clinical identification is for cardiac scan or the identifying pain associated with cardiac problems [0074]. Finally, the reference teaches that the processor 24 provides image processing relating quality assurance of the scan and also the image processing provides quality of imaging [0028][0037][0080].
Sharma do not specifically disclose the medical image diagnosis apparatus according to claim 1,
wherein the processing circuitry is further configured to obtain evaluation information regarding an estimated image estimated to be obtained by image capturing of the diagnosis target region under an image capturing condition different from the first image capturing condition, based on the subject information, and
wherein the evaluation information includes at least either one of first evaluation information regarding image quality of the estimated image and second evaluation information regarding uncertainty of disease classification estimated to be obtained in a case where a disease is classified based on the first medical image and the estimated image.
Gheorghita discloses disease classification using a machine-learned model wherein the disease is cardiovascular disease (CVD) [0002],
wherein a processing circuitry [0011] is configured to obtain evaluation information regarding an estimated image estimated to be obtained by image capturing of the diagnosis target region [0087][0090] under an image capturing condition, based on subject information (FIG. 6; [0042][0047][0052][0063])(FIG. 10; [0081], and
wherein the evaluation information includes second evaluation information regarding uncertainty of disease classification estimated to be obtained in a case where a disease is classified based on the first medical image and the estimated image [0103][0104][0105][0106].
It would have been obvious to one of ordinary skill within the art before the effective filing date of the claimed invention to adopt the teachings of Gheorghita to the medical image diagnosis apparatus of Sharma. The motivation is to gain an image diagnosis apparatus capable of evaluating an estimated image of the target region wherein the evaluation uses image capturing conditions relating to subject information and also provide evaluation information relating to the estimation of uncertainty of disease classification.
With regards to claim 4, Sharma, in view of Gheorghita, discloses the medical image diagnosis apparatus according to claim 3, wherein the estimated image is a medical image estimated to be captured in a case where an image of an unimaged portion within the diagnosis target region of the subject is captured (Sharma [0083] in view of the rejection of claim 3), and
wherein the processing circuitry obtains the evaluation information based on the first medical image and the estimated image (see the rejection of claim 3).
With regards to claim 5, Sharma, in view of Gheorghita, discloses the medical image diagnosis apparatus according to claim 3,
wherein the processing circuitry is further configured to generate the learned model by causing a model to execute learning (Sharma; [0044])(Gheorghita; Abstract),
wherein the processing circuitry obtains, based on subject information for learning including a medical image for learning, evaluation information for learning regarding an estimated image for learning that is estimated to be obtained by image capturing of a diagnosis target region under an image capturing condition different from an image capturing condition for learning under which the medical image for learning has been captured (see the rejection of claim 1 and 3),
wherein the processing circuitry causes the model to execute learning in such a manner that the evaluation information for learning improves based on the image capturing condition for learning, the subject information for learning, and the evaluation information for learning (Gheorghita; [0045]), and
wherein the processing circuitry determines the second image capturing condition by inputting the subject information and the first image capturing condition to the learned model (Sharma; [0006][0043]-[0045]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bunn (US 2024/0215945)
AlRegib et al. (US 2024/0170133)
Mavroeidis et al. (US 2024/0395025)
Vashist et bal. (US 2024/0212154)
Sato (US 2020/0126664)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUGH H MAUPIN whose telephone number is (571)270-1495. The examiner can normally be reached M-F 7:30 - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Uzma Alam can be reached at 571-272-3995. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUGH MAUPIN/ Primary Examiner, Art Unit 2884
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