DETAILED ACTION
Claims 1,3,4,5,7,6,8,12 and 9 and 10 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental process and math) without significantly more.
Claim(s) 1,3,4,5,11,12,13 and 9 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors).
Claim(s) 6,7 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors) as applied in claims 1 above further in view of Hara et al. (US 2013/0063565 A1), herein referred to as Hara I.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors) as applied in claims 1 above further in view of HARA (US 2018/0039856 A1), herein referred to as Hara II.
Response to Amendment
The amendment to claims and specification was received 2/13/2026. Claim 2 cancel. Claims 1,3-13 pending.
Response to Arguments
I. Claim Objection
Applicant’s arguments, see remarks, filed 2/13/2026, with respect to the claim objection of claims 1-8 have been fully considered and are persuasive. The objection of claims 1-8 has been withdrawn.
II. 35 USC 101
Applicants state that circuitry in claim 1 is not abstract. However, claim 1 still has an abstract idea and thus the 101 analysis proceeds to step 2A, prong 2, as detailed in the below 35 USC 101 rejection.
Applicants state that claim 9’s,10’s acquiring images is not abstract. The examiner respectfully disagrees since “acquire”1 is a mental learning process.
Applicants state that claims 1,9,10 are integrated into a practical application by sufficient sampling and identifying sample positions.
In response, are claims 1,9,10 treating a disease? improving the function of a computer? improving technology? and/or improving a technical field? at step 2A, prong 2? I believe applicants are improving the functioning of a computer in the computing technical field by making the display function (applicant’s fig. 3:S109: OUTPUT SAMPLING POSITIONS) of the computer readily comprehended or mastered by a user:
The tablet terminal that has received the first sampling position P31, second sampling position P32, and third sampling position P33 writes each of the sampling positions in the tumor characteristic prediction map. In this manner, the tumor characteristic prediction map is improved in the tablet terminal, and the user can easily2 recognize sampling positions.
III. 35 USC 103
Applicants state in page 9:
Danio teaches an apparatus with a different operation. As shown in Fig. 3, region 106 is an analysis target region where sub-regions 109A-D are set. As shown in Fig. 4 and described in [0050], the sub-regions are clustered on the basis of a feature-value distribution. S206 in Fig. 12 is asserted to identify a sampling point, but Danio teaches selection of a sub-region in [0206]. In Claim 1 the processing circuitry is configured to connect the plurality of regions based on the image feature amount to generate a first cluster in which at least some of the plurality of regions are collected and a second cluster related to the first cluster; and identify a sampling position based on the number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster. Nowhere in Danio is there any connection of a plurality of regions to generate first and second cluster or any sample position being identified based upon a number of connections. Sub-regions are not connected to each other, and no number of connections is involved with sample selection.
In response:
I am reading [0206] (DANJO US 2024/0153088 A1) as:
[0204] A medical image analysis method including:
[0205] setting sample regions in an analysis target region of an image obtained by imaging a biologically-originated sample, on the basis of an algorithm:
[0206] [[selecting3]] identifying at least one reference image from a plurality of reference images associated with a plurality of cases, on the basis of images of the sample [[regions4]] positions; and
[0207] outputting the selected reference image.
Thus DANJO teaches the claimed “sampling position” in view of said [0206] of claim 1 and thus is applicable under 35 USC 102(a)(2).
Applicants state in page 9:
Danio teaches an apparatus with a different operation. As shown in Fig. 3, region 106 is an analysis target region where sub-regions 109A-D are set. As shown in Fig. 4 and described in [0050], the sub-regions are clustered on the basis of a feature-value distribution. S206 in Fig. 12 is asserted to identify a sampling point, but Danio teaches selection of a sub-region in [0206]. In Claim 1 the processing circuitry is configured to connect the plurality of regions based on the image feature amount to generate a first cluster in which at least some of the plurality of regions are collected and a second cluster related to the first cluster; and identify a sampling position based on the number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster. Nowhere in Danio is there any connection of a plurality of regions to generate first and second cluster or any sample position being identified based upon a number of connections. Sub-regions are not connected to each other, and no number of connections is involved with sample selection.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “connection”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast, claim 1, line 7 says “connect the plurality of regions based on the image feature amount to generate a first cluster…and a second cluster”.
Applicants state in page 9:
Danio teaches an apparatus with a different operation. As shown in Fig. 3, region 106 is an analysis target region where sub-regions 109A-D are set. As shown in Fig. 4 and described in [0050], the sub-regions are clustered on the basis of a feature-value distribution. S206 in Fig. 12 is asserted to identify a sampling point, but Danio teaches selection of a sub-region in [0206]. In Claim 1 the processing circuitry is configured to connect the plurality of regions based on the image feature amount to generate a first cluster in which at least some of the plurality of regions are collected and a second cluster related to the first cluster; and identify a sampling position based on the number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster. Nowhere in Danio is there any connection of a plurality of regions to generate first and second cluster or any sample position being identified based upon a number of connections. Sub-regions are not connected to each other, and no number of connections is involved with sample selection.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “to each other” & “sample selection”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In contrast, claim 1, line 7 says “connect the plurality of regions based on the image feature amount to generate a first cluster…and a second cluster”.
In contrast, claim 1, line 10 states “identify a sampling position”
Applicants state in page 9:
Mortensen teaches finding a sampling position but connections among clusters are not used in finding the position. Intelligent scissoring is applied for boundary segmentation and also is not related to the processing circuitry noted above configured to connect clusters and identify a position based upon a number of connections. Claim 1 is patentable over Danio and Mortensen.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “finding the position”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
IV. New Claims
New claims 11 and 13 (reflecting an improvement as disclosed in applicant’s disclosure in information processing5) are not rejected under 35 USC 101 but are rejected under 35 USC 103, wherein DANJO (DANJO US 2024/0153088 A1) teaches claims 11,12,13 under the broadest reasonable interpretation consistent with applicant’s disclosure.
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 1,3,4,5,7,6,8,12 and 9 and 10 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental process and math) without significantly more.
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Step 0: establish broadest reasonable interpreted, shown throughout
Step 1: Claim 1 is a machine; claim 9 a process; claim 10 a manufacture
Step 2A, prong 1:
The claim(s) recite(s) mental-math judicial exception via claims 1 and 11:
Claim 1:
--acquire…a medical image…
divide the medical image…
calculate an image feature amount…
connect the plurality of regions…
identify a sampling position--:
Claim 1. (Currently Amended) A medical information processing device, comprising.
processing circuitry, the processing circuitry being configured to:
acquire 67 a medical image to be processed from an external device storing medical images;
divide the medical image into a plurality of regions;
calculate an image feature amount for each of the plurality of regions;
connect the plurality of regions based on the image feature amount to generate a first cluster in which at least some of the plurality of regions are collected and a second cluster related to the first cluster
identify a sampling position based on a number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster
Claim 11:
--generate…a tumor characteristic prediction map--
Claim 11. (New) The medical information processing8 device according to claim 1, wherein the processing circuitry is configured to generate9 and store10 a tumor characteristic prediction map11, and write12 the sampling position into13 the tumor characteristic prediction map.
Step 2A, prong 2:
This judicial exception is not integrated into a practical application because the additional elements (such as the claimed “medical information processing device” “processing circuitry” “a medical image” “regions” “external device”14 “sampling position”15 “cluster” “connections”16 “store” [“write”17]18) is not improving the computing field or treating a disease (a patient) via applicant’s disclosure:
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Step 2B:
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because each additional element (such as the claimed “medical information processing device” “processing circuitry” “a medical image” “regions” “external device”19 “sampling position”20 “cluster” “connections”21 “store” [“write”22]23) considered individually or with the mental process & math adheres to conventional practices as indicated in applicant’s specification’s background:
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Thus claims 11 and 13 are not rejected under 35 USC 101, since the claims reflect an improvement (computer function) under 35 USC 101.
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.
Claim(s) 1,3,4,5,11,12,13 and 9 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors).
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Re 1., Danjo teaches A medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) comprising24 (likewise) processing circuitry, the processing (“processor”25 [0038] last S) circuitry being configured (as shown in fig. 1:10) to:
acquire ((“cuts out”) [0053] 1st S: fig. 1:300: “SUB-REGION SETTING UNIT”)2627 a medical image to be processed from an external device (or likewise “The diagnosis DB 40 includes, for example, a memory28 device” [0031] penult S) storing medical images (or likewise “a database…store…A small-section image… associated with a plurality of cases29” [0038] 1st & 4th Ss);
divide (via said (“cuts out”) [0053] 1st S: fig. 1:300: “SUB-REGION SETTING UNIT”) the medical image into a plurality of regions;
calculate (via said “processor” [0038] last S) an image feature (“distribution” [0050]) amount for each of the plurality of (cut-out) regions;
connect the plurality of regions based on the image feature amount to generate a first cluster (or likewise “A plurality of sub-regions is clustered30 on the basis of a feature for each sub-region, to form a plurality of clusters “ [0050] 1st S) in which at least some of the plurality of (cut-out) regions (fig. 4) are collected (“from a human body” [0036[) and a second cluster (or likewise said “to form a plurality of clusters” [0050] 1st S) related to the first cluster (or likewise a cluster A sequentially related to cluster B in reverse order via “A descending order31 of a similarity for all the sub-regions A to C is 0.99, 0.95, 0.94, 0.92”, [0064] penult S, wherein “one…sub-region…may be…a…cluster”, [0050] 2nd S, of four square images via fig. 3: “SUB-REGION”: “RETRIEVED SMALL-SECTION IMAGE”: “A” “0.95” “0.92” “0.83”)
identify (via “identifying the small-section image selected by the user (S401)”, [0107]: fig. 14:S401: “SELECT SMALL-SECTION IMAGE DISPLAYED BY CASE INFORMATION DISPLAY UNIT”) a sampling32 position33 (or likewise “on34 the second screen portion…of the selected35 sample region36” [0189]) based (or “image of a sample region” [0053] 1st S) on a number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster
Danjo does not teach the difference37 of claim 1 of:
sampling (position38)39.
Mortensen teaches the difference40 of claim 1:
sampling (position)41, pg. 360:
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Since Danjo teaches a position, one of skill in the art of positions can make Danjo’s (pixels) be as Mortensen’s (pixels) predictably recognizing the change providing “a quicker, more accurate, and more reproducible general purpose tool for defining object boundaries within images” “on medical images”, Mortensen, pages 375,381, such as the on the medical images of Danjo:
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Re 3., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) according to claim [[2]] 1 , wherein the (processor) processing circuitry is configured to:
Identify (via “identifying the small-section image selected by the user (S401)”, [0107]: fig. 14:S401: “SELECT SMALL-SECTION IMAGE DISPLAYED BY CASE INFORMATION DISPLAY UNIT”) one of the first cluster (i.e., a region) and the second cluster (i.e., a region) which has a larger number of connections; and
identify (via “identifying the small-section image selected by the user (S401)”, [0107]: fig. 14:S401: “SELECT SMALL-SECTION IMAGE DISPLAYED BY CASE INFORMATION DISPLAY UNIT”) the sampling position (or “image of a sample region”42 [0053] 1st S via making Danjo’s (pixels) be as Mortensen’s (pixels)) within the (user) identified one of the first cluster (said A) and the second cluster (said B) having the larger number (“of a similarity…in some cases, and…similarity…in other cases”43 [0059] 5th S) of connections.
Re 4., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) according to claim [[2]] 1, wherein the second cluster (said B) is a cluster having the image feature amounts (in) common to the first cluster (A) and is44 separated (as shown in fig. 4) from the first cluster.
Re 5., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) according to claim [[2]] 1, wherein the medical image is45 a planar image (as shown in figure 2), and the (processor) processing circuitry is configured (as shown in fig. 1) to:
divide the medical image into the regions in a rectangular shape (fig. 2:106); and
count (or calculate) the number (“corresponding to the distance as a similarity” [0059 1st S) of (similarity-)connections on46 the basis of the number (fig. 4 has number-boxes) of regions in (similarity-)contact each other in either line contact (via similarity boxes in a line as shown in fig. 4: “EXAMPLE: RE-ARRANGE ALL RETRIEVAL RESULTS OF SUB-REGIONS IN DESCENDING ORDER OF SIMILARITY”) or point contact.
Re Claim 11. (New), Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim 1, wherein the processing circuitry is configured to
generate (“generates” [0027] 6th S) 4748 prediction4950 map51 (or likewise a generated value from a function “a feature value52 calculated” Danjo: [0038] 3rd S or likewise any equation/function as taught by Mortensen), and
write5354 (or likewise “an output55 unit 400” Danjo [0027] 2nd S or “Output: m” (m: feature cost maps as a function of the sampling position, p + k: in page 360: equations (8)(9)), Mortensen, pg. 364, ALGORITHM 1. Training on boundary segment, 3rd algorithm line: reproduced/annotated below) the sampling position (p+k) into the
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Re Claim 12. (New), Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim 1, comprising an image processing apparatus configured to generate a medical image of a subject (or likewise “ The output unit 400 generates screen data of the present application and causes a display (for example, a liquid crystal display device, an organic EL display device, or the like) to display the image data.” [0027] 6th S).
Re Claim 13. (New), Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim 1, wherein the processing circuitry is configured to
generate 56 (or likewise a generated value from a function “a feature value57 calculated” Danjo: [0038] 3rd S or likewise any equation/function as taught by Mortensen) to58 an external user59 device (or likewise “The medical image analysis apparatus 10 executes a medical image analysis application (hereinafter also referred to as the present application) used by a user of the medical image analysis apparatus 10.”, Danjo [0027] 4th S), and
transmit60 (or likewise going forwards to the next algorithm step via “the training algorithm61”, Mortensen, pg. 364, last para: ALGORITHM 1) the sampling position to6263 the external user device to be written64 (via algorithm 1) into the
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Claim 9 is rejected like claim 1:
Claim 9. (Currently Amended) A medical information processing method65 comprising:
acquiring66a medical image to be processed from an external device storing medical images;
dividing the medical image into a plurality of regions;
calculating an image feature amount for each of the plurality of regions;
connecting the plurality of regions based on the image feature amount to generatein which collected and a second cluster related to the first cluster
identifying a sampling position based on a number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster
Claim 10 is rejected like claims 1 and 9:
Claim 10. (Currently Amended) A computer-readable non-transitory storage medium67 storing a program for causing a computer to:
acquirea medical image to be processed from an external device storing medical images;
divide the medical image into a plurality of regions;
calculate an image feature amount for each of the plurality of regions;
connect the plurality of regions based on the image feature amount to generate a first cluster in which are collected and a second cluster related to the first cluster
identify a sampling position based on a number of connections in which the plurality of regions are connected in each of the first cluster and the second cluster .
Claim(s) 6,7 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors) as applied in claims 1 above further in view of Hara et al. (US 2013/0063565 A1), herein referred to as Hara I.
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Re 6., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim 1, wherein the medical image is a stereoscopic image, and
The (processor) processing circuitry is configured (as shown in fig. 1) to divide the medical image into the (“divisional” [0144] penult S) regions in a rectangular parallelepiped shape (fig. 2:106).
Danjo of the combination of Danjo and Mortensen does not teach
“stereoscopic…
parallelepiped”.
Hara I teaches:
stereoscopic (“[0050] (1-3) Binocular Stereoscopic Display of Microscopic Image”)…
parallelepiped (“formed by the three-dimensional image stack” [0293] last S).
Since Danjo of the combination of Danjo and Mortensen teaches a display (“The output unit 400 includes a pathological-tissue image display unit 410 and a case information display unit 420.” [0027] 3rd S), one of skill in the art of displays can make Danjo’s of the combination of Danjo and Mortensen be as Hara I’s predictably recognizing the change “to accurately provide the three-dimensional structure of a measurement specimen to users by applying technologies for generating a binocular stereoscopic image to a microscopic image group.”, Hara I [0005].
Claim 7 is rejected like claims 5 and 6:
Re 7., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim [[2]] 1, wherein the medical image is a stereoscopic image, and the processing circuitry is configured to:
divide the medical image into the regions in a rectangular parallelepiped shape; and
count the number of connections on the basis of the number of regions in surface contact, line contact, or point contact with each other.
Re 6., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device according to claim 1, wherein the medical image is a stereoscopic image, and
The (processor) processing circuitry is configured (as shown in fig. 1) to divide the medical image into the (“divisional” [0144] penult S) regions in a rectangular parallelepiped shape (fig. 2:106).
Re 5., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) according to claim 2, wherein the medical image is68 a planar image (as shown in figure 2), and the (processor) processing circuitry is configured (as shown in fig. 1) to:
divide the medical image into the regions in a rectangular shape (fig. 2:106); and
count (or calculate) the number (“corresponding to the distance as a similarity” [0059 1st S) of (similarity-)connections on69 the basis of the number (fig. 4 has number-boxes) of regions in (similarity-)contact each other in either line contact (via similarity boxes in a line as shown in fig. 4: “EXAMPLE: RE-ARRANGE ALL RETRIEVAL RESULTS OF SUB-REGIONS IN DESCENDING ORDER OF SIMILARITY”) or point contact.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over DANJO et al. (US 2024/0153088 A1) in view of Mortensen et al. (Interactive Segmentation with Intelligent Scissors) as applied in claims 1 above further in view of HARA (US 2018/0039856 A1), herein referred to as Hara II.
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Re 8., Danjo of the combination of Danjo and Mortensen teaches The medical information processing device (“apparatus 10” [0123] 2nd S: fig. 1: “MEDICAL IMAGE ANALYSIS APPARATUS”) according to claim 1, wherein the (processor) processing circuitry is configured (as shown in fig. 1) to identify (via “identifying the small-section image selected by the user (S401)”, [0107]: fig. 14:S401: “SELECT SMALL-SECTION IMAGE DISPLAYED BY CASE INFORMATION DISPLAY UNIT”) the sampling position (or “image of a sample region”70 [0053] 1st S via making Danjo’s (pixels) be as Mortensen’s (pixels))) on71 the basis of72
(A) a point (“indicated by the user via a click or the like in an image, as center coordinates thereof, may be set as a region of interest.” [0043] 8th S) that is the center (coordinates) of gravity of the (cut-out) regions or
(B) a point (“indicated by the user via a click or the like in an image, as center coordinates thereof, may be set as a region of interest.” [0043] 8th S) at which the sum of distances (“between cells” [0057]) from an (“outer (boundary)”[0081] 1st S) edge of the (cut-out) regions is shortest73 within the (cut-out) regions.
Danjo of the combination of Danjo and Mortensen does not teach:
gravity…
from…
is shortest.
Hara II teaches “gravity” of Markush alternative A (“an attention point (a point in the region of interest or a center of gravity of the region of interest)”[0027] 2nd S).
Since Danjo of the combination of Danjo and Mortensen teaches a center, one of skill in the art of centers can make Danjo’s of the combination of Danjo and Mortensen be as Hara II’s predictably recognizing the change “extracting the region of interest accurately”, Hara II [0027] 3rd S.
Conclusion
The prior art “nearest to the subject matter defined in the claims” (MPEP 707.05) made of record and not relied upon is considered pertinent to applicant's disclosure.
The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action.
Citation
Relevance
HU et al. (CN 114202550 A) with SEARCH machine translation
HU teaches a prediction feature (characteristic) map in the context of a tumour and characteristic, pg. 12,13:
--in order to improve the local space consistency of the prediction feature map , the output position of each attention mechanism module performs the element addition operation, so as to activate the effective feature of the tumour containing position information, the activation characteristic of each branch is connected to the feature mapping of the next branch from the upper branch by the splicing operation.—
as the closest to the claimed “tumor characteristic prediction map” of claim 11.
ZHENG (CN 116805536 A) with SEACH machine translation
ZHENG teaches a tumour prediction map constructing a tumour characteristic, pg. 4:
--using the cyclic convolution algorithm to perform expansion convolution and multi-scale sampling on the tumour lesion trend prediction map, constructing a tumour characteristic trend model can more accurately predict the tumour pathological change trend--
as the closest to the claimed “tumor characteristic prediction map” of claim 11.
GU et al. (Lessons Learned from Designing an AI-Enabled Diagnosis Tool for Pathologists)
GU teaches “tumor”-“red” (characteristic)-“Prediction map”: fig. 3:
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“(b) Prediction map, where red shows a high probability of tumor, and white shows a low probability of tumor, as predicted by the AI. The green and red boxes are areas of “normal” and “tumor”, as labeled by the pathologist. Recommendation boxes generated by clustering attention values are also visible on this map”
as the closest to the claimed “tumor characteristic prediction map” of claim 11.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS ROSARIO whose telephone number is (571)272-7397. The examiner can normally be reached Monday-Friday, 9AM-5PM EST.
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, Henok Shiferaw can be reached at 571-272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DENNIS ROSARIO/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
1 acquire: to gain for oneself through one's actions or efforts. to acquire learning. (Dictionary.com)
2 easy: readily comprehended or mastered. an easy language to learn. (Dictionary.com)
3 select: to choose in preference to another or others; pick out., wherein pick is defined: to attempt to find; seek out, wherein find is defined: to feel or perceive, wherein perceive is defined: to become aware of, know, or identify by means of the senses (Dictionary.com)
4 region: sphere, wherein sphere is defined: the place or environment within which a person or thing exists, wherein place is defined: position, situation, or circumstances (Dictionary.com)
5 information processing computing the combined (as shown in applicant’s fig. 8:right-side: a combined image) processing of numerical data, graphics, text, etc (as shown in fig. 8:right-side: M11, M13, P31) (Dictionary.com)
6 comma: the punctuation mark(,) indicating a slight pause in the spoken sentence and used where there is a listing of items or to separate a nonrestrictive clause or phrase from a main clause (Dictionary.com)
7 The crossed out text is not limiting in view of MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 4th para: The following types of claim language may raise a question as to its limiting effect (this list is not exhaustive [I am adding to the list Non-Limiting (nonrestrictive) comma Phrases: NLPs, such as --, via a communication network ,--):
• preamble (MPEP § 2111.02);
• clauses such as "adapted to," adapted for," "wherein," and "whereby" (MPEP § 2111.04, subsection I);
• contingent limitations (MPEP § 2111.04, subsection II);
• printed matter (MPEP § 2111.05); and
• functional language associated with a claim term (MPEP § 2181).
8 information processing: computing the combined processing of numerical data, graphics, text, etc (Dictioanry.com)
9 generate: Mathematics. to trace (a figure) by the motion of a point, straight line, or curve. (Dictionary.com)
10 store: Computers. to put or retain (data) in a memory unit. (Dictionary.com)
11 map: Mathematics. function. (Dictionary.com)
12 write: Computers. to transfer (information, data, programs, etc.) from storage to secondary storage or an output medium. (Dictionary.com)
13 “into” is a feature of information processing, defined above/below, wherein into is defined: to a point of contact with; against, wherein with is defined: in some particular relation to (especially implying interaction, company, association, conjunction, or connection). (Dictionary.com)
14 Implicit Information Processing (i.e., the technical field): “external device”: applicant’s disclosure, page 19 last para to page 20:
“The tablet terminal that has received the first sampling position P31, second sampling position P32, and third sampling position P33 writes each of the sampling positions in the tumor characteristic prediction map. In this manner, the tumor characteristic prediction map is improved in the tablet terminal, and the user can easily recognize sampling positions.”
15 “sampling position”, applicant’s disclosure, last page, last para:
“The medical information processing device 100 of the third embodiment has the same effects as the medical information processing device 100 of the first embodiment. The medical information processing device 100 of the third embodiment refers to the tumor characteristic prediction map in which sampling positions are identified. Accordingly, a tumor prediction map in which needle biopsy sampling positions are added to a user is generated. Therefore, a highly useful tumor prediction map can be easily produced.”
16 MEDICAL (biopsy) TREATMENT? No: there is no patent: “connections”: applicant’s disclosure, page 20, last para to page 21:
“In the medical information processing device 100 of each embodiment described above, in a case where a plurality of clusters of the same layer are generated, a sampling position is identified in the cluster with the largest number of connections, but a sampling position may be identified in a cluster other than the cluster with the largest number of connections. In this case, a plurality of sampling positions are identified for clusters of one layer, and these plurality of sampling positions may be prioritized. For example, superiority or inferiority may be determined depending on the number of connections of each cluster, and for example, the higher the number of connections, the higher the priority. For example, in a case in which it is difficult to perform a biopsy at the sampling position with the highest priority, when a puncture needle reaches the sampling position, for example, a biopsy may be performed using the next high priority sampling position in a case where the puncture needle passes through a major organ, for example, the heart.”, wherein patient is defined: a person who is under medical care or treatment, wherein biopsy is defined: A sample of tissue removed from a living body by a medical provider for diagnostic purposes. (Dictionary.com)
17 “write” see above “external device” footnote regarding an improvement in the tablet terminal being user-friendly
18 “[“write”]” represent deletion from this list of additional elements and is instead an additional element that makes the corresponding claim (11 & 13) integrated into a practical application at step 2A, prong 2.
19 “external device”: applicant’s disclosure, page 19 last para to page 20:
“The tablet terminal that has received the first sampling position P31, second sampling position P32, and third sampling position P33 writes each of the sampling positions in the tumor characteristic prediction map. In this manner, the tumor characteristic prediction map is improved in the tablet terminal, and the user can easily recognize sampling positions.”
20 “sampling position”, applicant’s disclosure, last page, last para:
“The medical information processing device 100 of the third embodiment has the same effects as the medical information processing device 100 of the first embodiment. The medical information processing device 100 of the third embodiment refers to the tumor characteristic prediction map in which sampling positions are identified. Accordingly, a tumor prediction map in which needle biopsy sampling positions are added to a user is generated. Therefore, a highly useful tumor prediction map can be easily produced.”
21 MEDICAL (biopsy) TREATMENT? No: there is no patent: “connections”: applicant’s disclosure, page 20, last para to page 21:
“In the medical information processing device 100 of each embodiment described above, in a case where a plurality of clusters of the same layer are generated, a sampling position is identified in the cluster with the largest number of connections, but a sampling position may be identified in a cluster other than the cluster with the largest number of connections. In this case, a plurality of sampling positions are identified for clusters of one layer, and these plurality of sampling positions may be prioritized. For example, superiority or inferiority may be determined depending on the number of connections of each cluster, and for example, the higher the number of connections, the higher the priority. For example, in a case in which it is difficult to perform a biopsy at the sampling position with the highest priority, when a puncture needle reaches the sampling position, for example, a biopsy may be performed using the next high priority sampling position in a case where the puncture needle passes through a major organ, for example, the heart.”, wherein patient is defined: a person who is under medical care or treatment, wherein biopsy is defined: A sample of tissue removed from a living body by a medical provider for diagnostic purposes. (Dictionary.com)
22 “write” see above “external device” footnote regarding an improvement in the tablet terminal being user-friendly
23 “[“write”]” represent deletion from this list of additional elements and is instead an additional element that makes the corresponding claim (11 & 13) integrated into a practical application at step 2A, prong 2.
24 BROAD CLAIM LANGUAGE: -ing (of “comprising” or any “-ing” word in this claim set): a suffix of nouns formed from verbs, expressing the action of the verb or its result, product, material, etc. (the art of building; a new building; cotton wadding ), wherein etc. is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted), wherein so is defined: likewise or correspondingly; also; too. (Dictionary.com)
25 processor: Computers. a controller, the key component of a computing device that contains the circuitry necessary to interpret and execute electrical signals fed into the device. (Dictionary.com)
26 comma: the punctuation mark(,) indicating a slight pause in the spoken sentence and used where there is a listing of items or to separate a nonrestrictive clause (--, via a communication network,--) or phrase from a main clause (claim 1) (Dictionary.com)
27 MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024], 4th para:
The following types of claim language may raise a question as to its limiting effect (this list is not exhaustive [I am adding to the non-exhaustive list Non-Limiting comma Phrases, NLPs: e.g., --, via a communication network,-- and this is struck-out representing a non-limiting phrase in claim 1):
• preamble (MPEP § 2111.02);
• clauses such as "adapted to," adapted for," "wherein," and "whereby" (MPEP § 2111.04, subsection I);
• contingent limitations (MPEP § 2111.04, subsection II);
• printed matter (MPEP § 2111.05); and
• functional language associated with a claim term (MPEP § 2181).
28 memory: Also called storage. Also called computer memory,. Computers. the capacity of a computer to store information subject to recall, wherein computer is defined: a programmable electronic device designed to accept data, perform prescribed mathematical and logical operations at high speed, and display the results of these operations, wherein display is defined: Digital Technology. to output (data) on a screen, wherein output is defined: Computers. to transfer (information) from internal storage to an external medium. (Dictionary.com)
29 case: a medical or surgical patient. (Dictionary.com)
30 cluster: to gather into a cluster or clusters, wherein gather is defined: to bring together into one group, collection, or place, wherein together is defined: into or in union, proximity, contact, or collision, as two or more things, wherein contact is defined: immediate proximity or association, wherein association is defined: connection or combination. (Dictionary.com)
31 order: a condition in which each thing is properly disposed with reference to other things and to its purpose; methodical or harmonious arrangement, where reference is defined: relation, regard, or respect.(Dictionary.com)
32 BROAD CLAIM LANGUAGE: -ing (of “sampling”): a suffix of nouns formed from verbs, expressing the action of the verb or its result, product, material, etc. (the art of building; a new building; cotton wadding ), wherein etc. is defined: and others; and so forth; and so on (used to indicate that more of the same sort or class might have been mentioned, but for brevity have been omitted), wherein so is defined: likewise or correspondingly; also; too. (Dictionary.com)
33 “sampling position” was narrowly interpreted in exact words; however, the MPEP 2131 Anticipation — Application of 35 U.S.C. 102 [R-08.2017], last para, penult S states “The elements must be arranged as required by the claim, but this is not an ipsissimis verbis test, i.e., identity of terminology is not required. In re Bond, 910 F.2d 831, 15 USPQ2d 1566 (Fed. Cir. 1990), wherein identity is defined: A. exact likeness in nature or qualities; B. Logic. an assertion that two terms refer to the same thing, wherein same is defined: agreeing in kind, amount, etc.; corresponding, wherein corresponding is defined: identical in all essentials or respects, wherein identical is defined: agreeing exactly. (Dictionary.com)
34 on: (used to indicate place, location, situation, etc.), wherein location is defined: a place or situation occupied, wherein place is defined: position, situation, or circumstances. (Dictionary.com)
35 select: to choose in preference to another or others; pick out., wherein pick is defined: to attempt to find; seek out, wherein find is defined: to feel or perceive, wherein perceive is defined: to become aware of, know, or identify by means of the senses (Dictionary.com)
36 region: sphere, wherein sphere is defined: the place or environment within which a person or thing exists, wherein place is defined: position, situation, or circumstances (Dictionary.com)
37 THE CLAIMED INVENTION AS A WHOLE:
Problem in applicant’s disclosure, pg. 2, 2nd para, last S:
“However, with this technique, it is difficult to narrow down a sampling region (sampling position) because it is impossible to identify which region best reflects tumor characteristics among a plurality of regions representing the same tumor characteristics.”
Solution to said problem, pgs 19,20, fig. 8: P31, P32,P33: “center of gravity of all the grid elements” (pg. 14, 1st S):
--In this manner, the tumor characteristic prediction map is improved in the tablet terminal, and the user can easily recognize sampling positions.—
Indications of obviousness:
Claim 1 does not claim the disclosed “center of gravity” “tumor” “tablet terminal” and “user”.
38 “sampling position” was narrowly interpreted in exact words; however, the MPEP 2131 Anticipation — Application of 35 U.S.C. 102 [R-08.2017], last para, penult S states “The elements must be arranged as required by the claim, but this is not an ipsissimis verbis test, i.e., identity of terminology is not required. In re Bond, 910 F.2d 831, 15 USPQ2d 1566 (Fed. Cir. 1990), wherein identity is defined: A. exact likeness in nature or qualities; B. Logic. an assertion that two terms refer to the same thing, wherein same is defined: agreeing in kind, amount, etc.; corresponding, wherein corresponding is defined: identical in all essentials or respects, wherein identical is defined: agreeing exactly. (Dictionary.com)
39 (italics) represent claim limitations already taught
40 THE CLAIMED INVENTION AS A WHOLE:
Problem in applicant’s disclosure, pg. 2, 2nd para, last S:
“However, with this technique, it is difficult to narrow down a sampling region (sampling position) because it is impossible to identify which region best reflects tumor characteristics among a plurality of regions representing the same tumor characteristics.”
Solution to said problem, pgs 19,20, fig. 8: P31, P32,P33: “center of gravity of all the grid elements” (pg. 14, 1st S):
--In this manner, the tumor characteristic prediction map is improved in the tablet terminal, and the user can easily recognize sampling positions.—
Indications of obviousness:
Claim 1 does not claim the disclosed “center of gravity” “tumor” “tablet terminal” and “user”.
41 (italics) represent claim limitations already taught
42 region: sphere, wherein sphere is defined: the place or environment within which a person or thing exists, wherein place is defined: position, situation, or circumstances (Dictionary.com)
43 similarity: the state of being similar; likeness; resemblance, wherein resemblance is defined: a degree, kind, or point of likeness, wherein point is defined: something that has position but not extension, as the intersection of two lines, wherein intersection is defined: Mathematics. Also called meet, product. the set of elements that two or more sets have in common. ∩, wherein in common is defined: Held equally, in joint possession or use, as in This land is held in common by all the neighbors . [Late 1300s], wherein joint is defined: joined or associated, as in relation, interest, or action, wherein join is defined: to come into contact or union with, wherein contact is defined: immediate proximity or association, wherein association is defined: connection or combination (Dictionary.com)
44 “ is” essentially means look at a figure (Dictionary.com)
45 “ is” essentially means look at a figure (Dictionary.com)
46 This “on” prepositional modifier has wide claim scope
47 ALTERNATIVE LANGUAGE: and: (used to connect alternatives). (Dictionary.com)
48 the MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024] -- Language (“and” & “tumor characteristic prediction”) that suggests or makes a feature or step optional (“and” and “tumor characteristic prediction” are each alternative language) but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art.--
49 “prediction” is a feature/property of the map: i.e., “map” comprises by definition “prediction: wherein map is defined: Mathematics. function wherein function is defined: Mathematics. Also called correspondence, map, mapping, transformation. a relation between two sets in which one element of the second set is assigned to each element of the first set, as the expression y = x 2 ; operator, wherein assign is defined: to designate; name; specify, wherein designate is defined: to mark or point out; indicate; show; specify, wherein indicate is defined: to be a sign of; betoken; evidence; show, wherein betoken is defined: to be or give a token or sign of; portend, wherein portend is defined: to indicate in advance; to foreshadow or presage, as an omen does, wherein omen is defined: prophetic significance; presage, wherein prophetic is defined: predictive; presageful or portentous; ominous, wherein predictive is defined: of or relating to prediction. . (Dictionary.com)
50ALTERNATIVE LANGUAGE: “tumor characteristic prediction” is a coordinate-adjective (meaning that both adjectives, “tumor characteristic” & “prediction”, coordinate equally to modify “map” and not both adjectives, “tumor characteristic” & “prediction”, modifying each other (as an cumulative adjective): applicant’s disclosure does not make clear that “characteristic” and “prediction” are related to each other, such as ~a classifier predicting a characteristic~ such that characteristic is the grammatical object of predicting ) and thus can be separated by alternative language “AND ”without changing the meaning (swapped in order) :--prediction AND tumor characteristic map— (no perceptible change in meaning), wherein AND is defined: (used to connect alternatives). (Dictionary.com)
51 map: Mathematics. function, when function is defined: a relationship in which an input value of a variable has a specifically calculated output value: for example, if the function of x is x 2 , the output will always be the square of whatever the value of x is. f, F (Dictionary.com)
52 value: Mathematics. a point in the range of a function; a point in the range corresponding to a given point in the domain of a function, wherein function is defined: a relationship in which an input value of a variable has a specifically calculated output value: for example, if the function of x is x 2 , the output will always be the square of whatever the value of x is. f, F, wherein output is defined: the quantity or amount produced, as in a given time, wherein produced is defined: to make or manufacture., wherein manufacture is defined: the making or producing of anything; generation. (Dictionary.com).
53 write: Computers. to transfer into a secondary storage device or output medium (Dictionary.com)
54 write: to express or communicate in writing; give a written account of, wherein express is defined: to represent by a symbol, character, figure, or formula. (Dictionary.com): this semantic sense of “write” is not consistent with applicant’s disclosure (pg. 19, last para) of “writes” and thus is not “taken” (MPEP 2111) under the broadest reasonable interpretation.
55 output: Computers.
A. information in a form suitable for transmission from internal to external units of a computer, or to an outside medium.
B. the process of transferring data from internal storage to an external medium, as paper or microfilm. (Dictionary.com)
56 map: Mathematics. function, wherein function is defined:
Mathematics.
A. Also called correspondence, map, mapping, transformation. a relation between two sets in which one element of the second set is assigned to each element of the first set, as the expression y = x 2 ; operator.
B. Also called multiple-value function. a relation between two sets in which two or more elements of the second set are assigned to each element of the first set, as y 2 = x 2 , which assigns to every x the two values y = + x and y = − x.
C. a set of ordered pairs in which none of the first elements of the pairs appears twice.
D. a relationship in which an input value of a variable has a specifically calculated output value: for example, if the function of x is x 2 , the output will always be the square of whatever the value of x is. f, F (Dictionary.com)
57 value: Mathematics. a point in the range of a function; a point in the range corresponding to a given point in the domain of a function, wherein function is defined: a relationship in which an input value of a variable has a specifically calculated output value: for example, if the function of x is x 2 , the output will always be the square of whatever the value of x is. f, F, wherein output is defined: the quantity or amount produced, as in a given time, wherein produced is defined: to make or manufacture., wherein manufacture is defined: the making or producing of anything; generation. (Dictionary.com).
58 to: (used for expressing addition or accompaniment) with. (Dictionary.com)
59 the MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024] -- Language (“external user”) that suggests or makes a feature or step optional (“external user” is alternative coordinate-adjective language: “external” does not modify “user” -external user- and instead modifies device: -external device- and the same analysis for “user”: -user device-) but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art.--
60 transmit: to send or forward, as to a recipient or destination; dispatch; convey. (Dictionary.com)
61 algorithm: Mathematics. a set of rules for solving a problem in a finite number of steps, such as the Euclidean algorithm for finding the greatest common divisor, wherein steps is defined: a move, act, or proceeding, as toward some end or in the general course of some action; stage, measure, or period, wherein proceeding is defined: the act of a person or thing that proceeds, wherein proceeds is defined: to move or go forward or onward, especially after stopping (Dictionary.com)
62 CLAIM SCOPE: regarding “to”: Applicant’s disclosure, last para:
--While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.--
63 to: (used for expressing addition or accompaniment) with. (Dictionary.com)
64 written: a past participle of write (Dictionary.com): participating in the action of “transmit”
65 The strike-out text is not limiting in view of MPEP 2143.03, 4th para: NLP
66 The strike-out text is not limiting in view of MPEP 2143.03, 4th para: NLP
67 Applicant’s disclosure, page 7, 3rd para:
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68 “ is” essentially means look at a figure (Dictionary.com)
69 This “on” prepositional modifier has wide claim scope
70 region: sphere, wherein sphere is defined: the place or environment within which a person or thing exists, wherein place is defined: position, situation, or circumstances (Dictionary.com)
71 This “on” prepositional modifier has broad claim scope under the broadest reasonable interpretation of claim 8
72 Markush element follows: A or B
73 “is shortest” is a modifier of “distances”: shortest distances
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