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 .
Election/Restrictions
Claims 6-9, 12 and 14 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 11/25/2025.
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 1-5, 10-11 and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims 1 and 13 recite to acquire a medical image and a first disease region in the medical image, derives a second disease region related to the first disease region in the medical image based on the medical image and the first disease region, updates the first disease region based on the medical image and the second disease region, updates the second disease region based on the medical image and the updated first disease region and repeats updates of the first and second disease regions until a predetermined end condition is satisfied.
The claim limitations of “derives” is a mental process of evaluation, a user can derive a second disease region from observing the medical image and the first disease region.
This judicial exception is not integrated into a practical application because the additional elements of “acquires a medical image and a first disease region” amounts to data gathering steps which is considered to be insignificant extra-solution activity (See MPEP 2106.05(g)). The element of “updates” and “repeats” are mere instructions to apply the exception using a generic computer component. All elements are recited to a high level of generality.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements as disclosed do not integrate the judicial exception into a practical application as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea.
Claim 11 recite an information processing method that acquires a medical image and a first disease region, derives a second disease region relates to the first disease region and the medical image, updates the first disease region based on the medical image and the second disease region, updates second disease region based on medical image and the updated first disease region and repeats update of the first and second diseases regions until a predetermined end condition is satisfied.
The claim limitations of “derives” is a mental process of evaluation, a user can derive a second disease region from observing the medical image and the first disease region.
This judicial exception is not integrated into a practical application because the additional elements of “acquires a medical image and a first disease region” amounts to data gathering steps which is considered to be insignificant extra-solution activity (See MPEP 2106.05(g)). The element of “updates” and “repeats” are mere instructions to apply the exception. See MPEP 2106.05(f).
The claims do not include additional elements that sufficient to amount to significantly more than the judicial exception because the additional elements as disclosed do not integrate the judicial exception into a practical application as they are mere instructions to apply the abstract idea, which cannot be inventive concept. See MPEP 2106.05(f).
Claim 2 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 2 recites the same abstract idea of claim 1. The claim recites the additional limitation of “the processor performs update of the first disease region and derivation and update of the second disease region by using a first discriminative model that has been trained to output the second disease region in a case in which the medical image and the first disease region are input, and a second discriminative model that has been trained to output the first disease region in a case in which the medical image and the second disease region are input”, which is merely elaborating on the abstract idea, by further specifying an additional element recited at a high-level of generality and mere instructions to apply the abstract idea, therefore, does not amount to significantly more than the abstract idea.
Claim 3 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 3 recites the same abstract idea of claim 1. The claim recites the additional limitation of “processor performs update of the first disease region and derivation and update of the second disease region further based on at least one of information representing an anatomical region of an organ including the first and second disease regions or clinical information”, which is merely elaborating on the abstract idea, by further specifying an additional element recited at a high-level of generality, therefore, does not amount to significantly more than the abstract idea.
Claim 4 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 4 recites the same abstract idea of claim 1. The claim recites the additional limitation of “processor acquires the first disease region by extracting the first disease region from the medical image”, which is merely elaborating on the abstract idea, by further specifying an additional element recited at a high-level of generality, therefore, does not amount to significantly more than the abstract idea.
Claim 5 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 5 recites the same abstract idea of claim 1. The claim recites the additional limitation of “processor derives quantitative information for at least one of the first disease region or the second disease region, and displays the quantitative information”, which is merely elaborating on the abstract idea, by further specifying an additional element recited at a high-level of generality, therefore, does not amount to significantly more than the abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Akahori (US 2020/0104996 A1): paragraph [0050] acquiring CT image and discriminates a thrombus region or an infarction region in the CT image, paragraph [0023] discriminating a second disease region from the medical image, paragraph [0052] CT image B0, from which disease regions are to be extracted, from the image storage server 3 in order to extract the disease regions such as a thrombus region and an infarction region.
Akahori (US 2020/0104995 A1): paragraphs [0008] and figure 13 provided a disease region extraction apparatus comprising: an image acquisition unit that acquires a first image obtained by capturing an image of a subject that has developed a disease; an estimated image derivation unit that estimates a second image, whose type is different from a type of the first image, from the first image to derive an estimated image; and a disease region extraction unit that extracts a disease region from the estimated image derived by the estimated image derivation unit.
Kim et al. (US 2019/0269359 A1): figure 1 and paragraph [0050] receiving a first image and a second image of a first patient whose acute cerebral infarction onset time is not identified; a step S400 of extracting an infarction region image from the second image 20; a step S600 of aligning the second image with the first image 10; a step S800 of defining an infarction region in the first image, based on a result of the alignment of the second image with the first image; a step S1000 of extracting feature information of the first patient, from the infarction region in the first image 10; a step S1200 of comparing the extracted feature information with reference data; and a step S1400 of calculating an amount of time that has elapsed since the acute cerebral infarction onset time. In some embodiments, each of the above described steps is performed by a computer or a processor. According to the above described operations, as shown in FIG. 2, based on the first image 10, which is a fluid-attenuated inversion recovery image, and the second image 20, which is a diffusion-weighted image, an infarction region image 21 is extracted, and an infarction region is defined in a registered fluid-attenuated inversion recovery image 11. Further, a ratio map 30 is generated based on the registered fluid-attenuated inversion recovery image 11, and feature information 40 is extracted.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IRIANA CRUZ whose telephone number is (571)270-3246. The examiner can normally be reached 10-6.
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/IRIANA CRUZ/ Primary Examiner, Art Unit 2681