DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/02/2026 has been entered.
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(s) (IDS) submitted on 02/24/2026 and 06/26/2026 is/are being considered by the examiner.
Response to Amendment
The Amendment filed 05/18/2026 has been entered. Claim 3 has been cancelled. New claims 14 and 15 have been added. Therefore, claims 1-2 and 4-15 remain pending in the application.
Response to Arguments
Applicant’s arguments, filed 05/18/2026, have been fully considered but are not persuasive.
With respect to the 35 U.S.C. 101 abstract idea rejection, see pages 9-10, the Applicant asserts that claim 1 is not merely directed to human reading or mental judgement, but to a specific processor-executed sequence including relationship-based linguistic analysis of report sentences and responsive image recognition of diagnostic images. They assert that claim 1 recites a specific technical workflow in which the processor automatically generates a key image and attaches the key image to the interpretation report to generate a single interpretation report and store the single interpretation report in a medical report database. They further assert that the claimed invention ensures that the visual content is reliably tied to the textual diagnosis in the report. This provides a practical application in the medical-report generation process by automatically linking diagnostic text with a corresponding recognized image region, eliminating manual image selection or cropping, reducing the amount of image data associated with the report by storing the generated key image with the report, and streamlining storage and retrieval of the single interpretation report in the medical database.
The Examiner respectfully disagrees. The claim, under its broadest reasonable interpretation, recites a system and a method for receiving data (i.e. a series of sentences), analyzing that data with natural language analysis, extracting data, analyzing the extracted data, analyzing image data based upon the extracted data, extracting data from the image, and combining the extracted image data with the original text data. This is an abstract idea in the form of certain methods of organizing human activity (i.e. mental processes such as observation, evaluation, judgement, and opinion). The steps of receiving a series of sentences, converting the series of sentences into word strings, extracting words from the word strings, determining relationships between the words, looking at an image and associating parts of the image with the words and their relationships, and combining the image and the words into a single report could be performed by a human using pen and paper or by purely mental reasoning, save for the recitation of generic computing components. The step of accepting a series of sentences is insignificant data gathering (or pre-solution activity), and is a generic computer step. Further, the claims do not integrate the judicial exception into a practical application. The recitation of “at least one processor”, “at least one memory”, and “a medical report database” are generic instructions to perform the abstract idea on a computer or using computer devices and do not impose a meaningful limit on the judicial exception. The “at least one processor”, “at least one memory”, and “a medical report database” are recited as such high-levels of generality and are merely used as tools to perform the abstract idea faster or more efficiently. Based on the plain reading of the claim itself, there is no reasonable improvement to the functions of the data receiving, the data analysis, the data extraction, the data modification, the processors, the memory, or to any other technology or technical field. The claims do not include any additional elements that amount to significantly more than the judicial exception. The claims, as written and amended, do not include more than mere instructions to perform the abstract method using generic computer components. Hence, Applicant’s arguments are not persuasive. With respect to the 35 U.S.C. 103 rejection, on pages 10-14, of claims 1-13 under Sohma (US Patent No. 10,628,476), in view of Kubo et al. (US Patent Application Publication No. 2017/0069084), hereinafter referred to as Kubo, the Applicant asserts that Kubo does not disclose or suggest “attach the key image to the interpretation report to generate a single interpretation report, and store the single interpretation report in a medical report database”. They also assert that Sohma does not disclose or suggest using extracted expressions to trigger subsequent image recognition on a plurality of diagnostic images. The Applicant also asserts that the combination of Sohma and Kubo therefore fails to disclose or suggest “determine whether the two or more words include a word representing a region of interest in the plurality of diagnostic images and a word representing facticity of the region of interest in the plurality of diagnostic images on the basis of the relationship of the two or more words; in response to the facticity affirming existence of the region of interest, perform image recognition on the plurality of diagnostic images to extract the region of interest corresponding to the two or more words to automatically generate a key image among the plurality of diagnostic images that is associated with the two or more words”.
In response to Applicant’s argument that Kubo does not disclose or suggest “attach the key image to the interpretation report to generate a single interpretation report, and store the single interpretation report in a medical report database”, Kubo Fig. 2 S206 shows displaying the image itself, Kubo paragraphs [0057]-[0059] speaks upon displaying the text from the interpretation report alongside the medical image, thereby attaching them together in a single display. Also, Kubo paragraph [0108] states: "On the server side, a medical image and an interpretation report are acquired based on the selected case number, and the above-described processing is performed to finally determine the display position of the interpretation text (steps S201 to S205). Next, the server transmits the medical image, the interpretation report, the interpretation text, and the display position of the interpretation text to the client side. On the client side, the medical image and the interpretation text are displayed based on the transmitted contents (step S206).” This shows that client and server side are in communication with each other, and Kubo paragraph [0048] states: “In step S202, the interpretation report acquisition unit 42 acquires an interpretation report corresponding to the medical image read out in step S201 from the database 22 via the communication IF 31 and the LAN 21. In this embodiment, the interpretation report is created and registered in the database 22 in the following way.” This states that the following paragraphs show how the interpretation report is created and registered (i.e. saved, stored) within the medical database, even further explained by Kubo paragraph [0050]: “The medical image display apparatus 10 saves the interpretation text and the position-of-interest information (or region-of-interest information) in the database 22 in association.” In response to Applicant’s argument that the combination of Sohma and Kubo fails to disclose or suggest “determine whether the two or more words include a word representing a region of interest in the plurality of diagnostic images and a word representing facticity of the region of interest in the plurality of diagnostic images on the basis of the relationship of the two or more words; in response to the facticity affirming existence of the region of interest, perform image recognition on the plurality of diagnostic images to extract the region of interest corresponding to the two or more words to automatically generate a key image among the plurality of diagnostic images that is associated with the two or more words”, Sohma discloses the first portion through paragraph [0102]: “As “term” information, information belonging to categories such as region name, lesion/abnormality name, and disease is obtained with respect to descriptions. As “supplementary expression” information, information belonging to categories such as shape and size and subcategories such as concreteness is obtained with respect to descriptions. As “perceptual expression” information, information corresponding to direct expressions of visual perception, recognition/possibility, and the like such as “considered”, “seen”, and “suspected” and information belonging to categories such as expression of confirmation of existence (presence/absence) including “exists” and “accompanied” are obtained with respect to descriptions and combinations of them.” This paragraph shows that natural language processing performed by Sohma associates words with regions of interest (e.g. region name, visual perception, etc.) and facticity affirming existence (e.g. perceptual expression, recognition, confirmation of existence, etc.). Kubo discloses the second portion of these limitations with Kubo Fig. 3 reference characters 320 and 321. These reference characters show the facticity affirming existence of the region of interest through the report itself and the position of interest within the image. Kubo further shows reference character S204 in Fig. 2, which discloses performing image recognition to extract a region of interest. Kubo paragraph [0052] states: "In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest.” Kubo then shows reference character S206 in Fig. 2, stating that the medical image is displayed along with the report. Kubo para [0057] states: “In step S206, the display processing unit 46 overlays the character string display region including some or all of the character strings of the interpretation text acquired in step S202 at the display position determined in step S205 on the medical image acquired in step S201. The display processing unit 46 performs display control to display, on the display unit 36, the medical image with the character string display region including the interpretation text being overlaid.” This shows that both the interpretation report text and the medical image are shown together, thereby automatically generating a key image. Hence, Applicant’s arguments are not persuasive.
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.
Claim(s) 1-2 and 4-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1 and 11 recite “accept a series of sentences”, “perform natural-language analysis on the series of sentences”, “extract two or more words included in the words strings and specify a relationship of two or more words”, “determine whether the two or more words include a word representing a region of interest” “in response to the facticity affirming existence of the region of interest”, perform image recognition on the plurality of diagnostic images”, and “attach the key image to the interpretation report”. These limitations, as drafted, are a process that, under a broadest reasonable interpretation, covers the abstract idea of “mental processes” because they cover concepts performed in the human mind, including observation, evaluation, judgement, and opinion. See MPEP 2106.04(a)(2). That is, other than reciting “at least one processor” and “at least one memory”, nothing in the claimed elements preclude the steps from practically being performed by a person reading an interpretation report written by a medical professional, analyzing the report to create relationships between the words, looking at images corresponding to the report, and deciding to append a key image to the report based on the image coinciding with the report.
This judicial exception is not integrated into a practical application because the additional elements “at least one processor” and “at least one memory” are all recited at a high- level of generality. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims as a whole are directed to an abstract idea (Step 2A, prong two).
Claims 1 and 11 do not include any additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical applications, the additional elements of “at least one processor” and “at least one memory” amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (Step 2B).
Dependent claims 2, 4-10, and 12-13 are directed to the words in the interpretation report and their relationships among themselves and to the images. That is, nothing in the claimed elements preclude the steps from practically being performed by a person reading an interpretation report written by a medical professional, analyzing the report to create relationships between the words, looking at images corresponding to the report, and deciding to append a key image to the report based on the image coinciding with the report.
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.
Claim(s) 1-2 and 4-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sohma (US Patent No. 10,628,476), in view of Kubo et al. (US Patent Application Publication No. 2017/0069084), hereinafter referred to as Kubo.
Regarding claim 1, Sohma discloses an information processing apparatus comprising: at least one processor (Sohma Fig. 1, element 101);
and at least one memory that stores a command for the at least one processor to execute (Sohma Fig. 1, elements 102 and 103);
wherein the at least one processor is configured to: accept a series of sentences of an interpretation report including a diagnosis result corresponding to a plurality of diagnostic images, wherein the series of sentences are text data that describe the plurality of diagnostic images (Sohma para [0008], Sohma Fig. 4 reference character S401, and Sohma Fig. 5A shows an example of the report referring to the image(s));
perform natural-language analysis on the series of sentences to convert the series of sentences into word strings, wherein the natural-language analysis includes analyzing relationships between words in the series of sentences (Sohma Fig. 4 reference character S402-S403, Sohma Fig. 5B shows the words/word strings created from Sohma Fig. 5A, and Sohma para [0102]-[0103]);
extract two or more words included in the word strings and specify a relationship of two or more words included in the word strings ("The natural language processing unit 369 is a processing unit which analyzes medical texts. The natural language processing unit 369 has an analyzing unit 370 as a processing unit which analyzes texts. The analyzing unit 370 performs morphological analysis to obtain terms used in texts on a word basis and syntax analysis to analyze the modification relations between words. Morphological analysis is analysis processing for obtaining the original notations of words such as original or basic forms by dividing character strings in texts, classifying the words into part of speech, and removing conjugation, inflection, and the like. This analyzes a text into the form of word strings," Sohma para [0092], Sohma para [0103], and Sohma Fig. 5B and 6A show the extracted words);
determine whether the two or more words include a word representing a region of interest in the plurality of diagnostic images and a word representing facticity of the region of interest in the plurality of diagnostic images on the basis of the relationship of the two or more words (As “term” information, information belonging to categories such as region name, lesion/abnormality name, and disease is obtained with respect to descriptions. As “supplementary expression” information, information belonging to categories such as shape and size and subcategories such as concreteness is obtained with respect to descriptions. As “perceptual expression” information, information corresponding to direct expressions of visual perception, recognition/possibility, and the like such as “considered”, “seen”, and “suspected” and information belonging to categories such as expression of confirmation of existence (presence/absence) including “exists” and “accompanied” are obtained with respect to descriptions and combinations of them," Sohma para [0102]).
However, Sohma fails to disclose in response tothe facticity affirming existence of the region of interest, perform image recognition on the plurality of diagnostic images to extract [[ a ]] the region of interest corresponding to the two or more words to automatically generate [[the]] a key image among the plurality of the diagnostic images that is associated with the two or more words; and attach the key image to the interpretation report to generate a single interpretation report and store the single interpretation report in a medical report database. Kubo teaches an information processing apparatus for medical image display.
Kubo teaches in response tothe facticity affirming existence of the region of interest (Kubo Fig. 3 reference character 320 and 321), perform image recognition on the plurality of diagnostic images to extract [[ a ]] the region of interest corresponding to the two or more words (Kubo Fig. 2 reference character S204 and "In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest," Kubo para [0052]) to automatically generate [[the]] a key image among the plurality of the diagnostic images that is associated with the two or more words (Kubo Fig. 2 reference character S206 and Kubo para [0057]);
and attach the key image to the interpretation report to generate a single interpretation report and store the single interpretation report in a medical report database (Kubo Fig. 2 S206 and Kubo paras [0057]-[0059] AND "On the server side, a medical image and an interpretation report are acquired based on the selected case number, and the above-described processing is performed to finally determine the display position of the interpretation text (steps S201 to S205). Next, the server transmits the medical image, the interpretation report, the interpretation text, and the display position of the interpretation text to the client side. On the client side, the medical image and the interpretation text are displayed based on the transmitted contents (step S206)," Kubo para [0108], Kubo para [0048], and “The medical image display apparatus 10 saves the interpretation text and the position-of-interest information (or region-of-interest information) in the database 22 in association,” Kubo para [0050]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modified Sohma’s disclosure of a medical text information processor by including Kubo’s teaching of a medical image and text processor. Determining an anatomical region that corresponds to the keywords or series of sentences allows for any user to easily understand the connection between the two items. This combination, alongside the attachment of the determined regional image, would result in providing the user of the device with an easier to interpret diagnostic report, and therefore would have been obvious to one of ordinary skill in the art.
Regarding claim 2, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the two or more words include at least two words from among a word representing a region of interest, a word representing facticity, a word representing change information, a word representing a position, a word representing a size, a word representing a characteristic, or a word representing an imaging condition ("The term expression obtaining unit 365 obtains terms appearing in the text, supplementary expressions corresponding to the terms, and perceptual expressions corresponding to the terms and the supplementary expressions based on the morphological analysis and syntax analysis results and dictionary data. The results obtained by this processing are included in FIG. 5B, and are indicated in the “term”, “supplementary expression”, and “perceptual expression” columns. As “term” information, information belonging to categories such as region name, lesion/abnormality name, and disease is obtained with respect to descriptions. As “supplementary expression” information, information belonging to categories such as shape and size and subcategories such as concreteness is obtained with respect to descriptions. As “perceptual expression” information, information corresponding to direct expressions of visual perception, recognition/possibility, and the like such as “considered”, “seen”, and “suspected” and information belonging to categories such as expression of confirmation of existence (presence/absence) including “exists” and “accompanied” are obtained with respect to descriptions and combinations of them," Sohma para [0102]).
Regarding claim 4, Sohma, in view of Kubo, discloses all of the limitations of claim 2. Sohma further discloses wherein the word representing the change information includes a word representing change information on at least one of a size or an amount (“In step S1005, information of terms and attribute expressions (supplementary expressions and perceptual expressions) is obtained, which has undergone information classification changes and attribute classification changes/improvements, from revision/improvement records. The classifying structuring unit 363 executes this processing,” Sohma para [0140]).
Regarding claim 5, Sohma, in view of Kubo, discloses all of the limitations of claim 2. However, Sohma does not disclose wherein the at least one processor extracts the candidate for the key image from the image on the basis of the position.
Kubo teaches wherein the at least one processor extracts the candidate for the key image from the image on the basis of the position ("In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest," Kubo para [0052]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Extracting the key image based upon the positional words found in the given string of sentences would ensure that the text report and the medical image correctly correspond to each other. This would make their relationship easier to absorb to any user of the diagnostic device. Therefore, this combination would have been obvious to one of ordinary skill in the art.
Regarding claim 6, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the at least one processor is configured to: accept two or more types of images of which the imaging conditions are different (“The medical image interpreter 202 is a radiologist who interprets CT images, MRI images, and the like,” Sohma para [0049].) This shows that the images that are then submitted to the interpretation processing unit (shown in Fig. 2) can be of multiple types.
However, Sohma does not disclose extract the candidate for the key image from the two or more types of images.
Kubo teaches extract the candidate for the key image from the two or more types of images (“In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest,” Kubo para [0052]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Being able to accept multiple different types of images as inputs and extracting the key image from these creates a more versatile device that can then be used with a multitude of medical imaging technologies. Therefore, this would have been obvious to one of ordinary skill in the art.
Regarding claim 7, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the image is a medical image ("In this embodiment, on the premise of such an environment, a doctor performs image diagnosis by using medical images such as CT and MRI images, and summarizes and writes the diagnosis result as an interpretation report," Sohma para [0047];
the two or more words include a word representing a disease name (“As “term” information, information belonging to categories such as region name, lesion/abnormality name, and disease is obtained with respect to descriptions,” Sohma para [0102]).
However, Sohma does not disclose and the at least one processor extracts the candidate for the key image on the basis of the disease name.
Kubo teaches and the at least one processor extracts the candidate for the key image on the basis of the disease name (“For example, when an interpretation text is created for a right lung disease, not only the region occupied by the right lung field but also other organs (for example, the left lung field and the bronchus) that can be related to the disease may be taken into consideration when determining the display position of the interpretation text,” Kubo para [0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Allowing for the key image to be chosen based upon the disease name identified in the given series of sentences would ensure that the image or images included encapsulated everything that could be affected by said disease. Many diseases affect multiple parts of the body, so including this limitation allows for all of the possible related images to be shown. Therefore, this would have been obvious to one of ordinary skill in the art.
Regarding claim 8, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the two or more words include a word representing a region of interest, and a word representing a malignancy grade of the region of interest (“As “supplementary expression” information, information belonging to categories such as shape and size and subcategories such as concreteness is obtained with respect to descriptions. As “perceptual expression” information, information corresponding to direct expressions of visual perception, recognition/possibility, and the like such as “considered”, “seen”, and “suspected” and information belonging to categories such as expression of confirmation of existence (presence/absence) including “exists” and “accompanied” are obtained with respect to descriptions and combinations of them," Sohma para [0102]).
However, Sohma does not disclose and the at least one processor is configured to: determine that the association of the key image is necessary in a case where the malignancy grade affirms malignancy of the region of interest; and determine that the association of the key image is not necessary in a case where the malignancy grade denies the malignancy of the region of interest.
Kubo teaches and the at least one processor is configured to: determine that the association of the key image is necessary in a case where the malignancy grade affirms malignancy of the region of interest (“In step S203, the keyword extraction unit 43 extracts a keyword set in advance from the interpretation text read out in step S202 by keyword matching,” Kubo para [0051] and “In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest,” Kubo para [0052];
and determine that the association of the key image is not necessary in a case where the malignancy grade denies the malignancy of the region of interest (“In step S203, the keyword extraction unit 43 extracts a keyword set in advance from the interpretation text read out in step S202 by keyword matching,” Kubo para [0051] and “In step S204, the region acquisition unit 44 extracts an anatomical region corresponding to the keyword extracted in step S203 from the medical image acquired in step S201, and acquires the region as a region related to the region of interest,” Kubo para [0052].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Allowing for the key image to be chosen and potentially included based upon the malignancy grade identified in the given series of sentences would ensure that the image or images included encapsulated everything affected by the condition that results in the malignancy grade. If the malignancy grade is higher, it could potentially be present in a larger area or in different areas of the body, so including this limitation allows for all of the possible related images to be shown. Therefore, this would have been obvious to one of ordinary skill in the art.
Regarding claim 9, Sohma, in view of Kubo, discloses all of the limitations of claim 1. However, Sohma does not disclose wherein the at least one processor is configured to: display the candidate for the key image on a display; accept an operation by a user; and associate the candidate of the key image with the series of sentences, as the key image according to the operation.
Kubo teaches wherein the at least one processor is configured to: display the candidate for the key image on a display (“The display processing unit 46 performs display control to display, on the display unit 36, the medical image,” Kubo para [0057]);
accept an operation by a user (“The character string display region of the interpretation text may be moved in accordance with an operation input of the user,” Kubo para [0065]);
and associate the candidate of the key image with the series of sentences, as the key image according to the operation (“In step S206, the display processing unit 46 overlays the character string display region including some or all of the character strings of the interpretation text acquired in step S202 at the display position determined in step S205 on the medical image acquired in step S201,” Kubo para [0057]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Showing the medical key image associated with the given series of sentences alongside the aforementioned given series of sentences on a display allows for any user to understand the connection between the two. Allowing for accepting an operation from a user in order to affect the report also lets the interaction between user and the full output (key image and given series of sentences) be more user-friendly. This combination would result in providing the user of the device with an easier to understand diagnostic report, and therefore would have been obvious to one of ordinary skill in the art.
Regarding claim 10, Sohma, in view of Kubo, discloses all of the limitations of claim 1. However, Sohma does not disclose wherein the image is a three-dimensional image, and the at least one processor is configured to: display, as the candidate for the key image, a slice image at any slice position of the three-dimensional image on a display; accept a change of the slice position of the candidate for the key image by a user; and associate the slice image at the changed slice position with the series of sentences, as the key image.
Kubo teaches wherein the image is a three-dimensional image (Kubo Fig. 8, Fig. 10A, and Fig. 10B all show three-dimensional images and “In this embodiment, the display processing unit 46 displays the interpretation text associated with the region of interest together with each slice image existing within a predetermined distance from the region of interest in a direction perpendicular to the cross section of the slice image. For this reason, even if a disease is distributed three-dimensionally, the user can easily grasp the correspondence between the interpretation text and the region with the disease,” Kubo para [0076];
and the at least one processor is configured to: display, as the candidate for the key image, a slice image at any slice position of the three-dimensional image on a display (“In this embodiment, the display processing unit 46 displays the interpretation text associated with the region of interest together with each slice image existing within a predetermined distance from the region of interest in a direction perpendicular to the cross section of the slice image. For this reason, even if a disease is distributed three-dimensionally, the user can easily grasp the correspondence between the interpretation text and the region with the disease,” Kubo para [0076];
accept a change of the slice position of the candidate for the key image by a user (“In the above-described embodiment, a position indicating specific coordinates in the medical image is recorded and used as the position-of-interest information of the interpretation report. However, the position-of-interest information is not limited to this. For example, the user may set the position of interest as a range (to be referred to as a range of interest hereinafter). More specifically, an ROI (Region Of Interest) or VOI (Volume Of Interest) is set,” Kubo para [0077];
and associate the slice image at the changed slice position with the series of sentences, as the key image (“An example in which an ROI is set will be described with reference to FIGS. 9A, 9B, and 9C. The medical image 410 and the broken lines 411 in FIGS. 9A, 9B, and 9C are the same as those shown in FIG. 4. A range of interest corresponding to the interpretation text of the medical image is set as an ROI 415 by the user. The character string display region display position determination method in this case will be described.),” Kubo para [0078].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Allowing for a three-dimensional image to be taken as an input and have individual two-dimensional slices of the original image be displayed as a key image alongside the corresponding given series of sentences would allow for better representation of the diagnosis through the displayed images, as slices of the three-dimensional image could be chosen along any axis. This freedom of choosing image slices, as well as allowing for a user to change the slice position themselves, increases the user-friendliness of the device as well as resulting in a better understood diagnostic report.
Regarding claim 11, method claim 11 and system claim 1 are related as system and method of using same, with each claimed element’s function corresponding to the system step. Accordingly, claim 11 is similarly rejected under the same rationale as applied above with respect to system claim.
Regarding claim 12, Sohma, in view of Kubo, discloses a non-transitory, computer-readable tangible recording medium which records thereon a program for causing, when read by a computer, the computer to execute the information processing method according to claim 11 (“Embodiment(s) of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be referred to more fully as a ‘non-transitory computer-readable storage medium’) to perform the functions of one or more of the above-described embodiment(s) and/or that includes one or more circuits (e.g., application specific integrated circuit(ASIC)) for performing the functions of one or more of the above-described embodiment(s), and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s) and/or controlling the one or more circuits to perform the functions of one or more of the above-described embodiment(s)," Sohma para [0159]).
Regarding claim 13, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the image is a medical image ("In this embodiment, on the premise of such an environment, a doctor performs image diagnosis by using medical images such as CT and MRI images, and summarizes and writes the diagnosis result as an interpretation report," Sohma para [0047];
the two or more words include a word representing an imaging condition and a word representing a characteristic indicating a lesion ("As “term” information, information belonging to categories such as region name, lesion/abnormality name, and disease is obtained with respect to descriptions. As “supplementary expression” information, information belonging to categories such as shape and size and subcategories such as concreteness is obtained with respect to descriptions. As “perceptual expression” information, information corresponding to direct expressions of visual perception, recognition/possibility, and the like such as “considered”, “seen”, and “suspected” and information belonging to categories such as expression of confirmation of existence (presence/absence) including “exists” and “accompanied” are obtained with respect to descriptions and combinations of them," Sohma para [0102]).
However, Sohma does not disclose and the at least one processor extracts the candidate for the key image on the basis of the imaging condition and the characteristic.
Kubo teaches and the at least one processor extracts the candidate for the key image on the basis of the imaging condition and the characteristic (“For example, when an interpretation text is created for a right lung disease, not only the region occupied by the right lung field but also other organs (for example, the left lung field and the bronchus) that can be related to the disease may be taken into consideration when determining the display position of the interpretation text,” Kubo para [0060]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sohma’s disclosure of a medical text information processor with Kubo’s teaching of a medical image and text processor. Allowing for the key image to be chosen based upon the imaging condition and a characteristic indicating a lesion identified in the given series of sentences would ensure that the image or images included encapsulated everything that could be affected by said lesion. Lesions can affect multiple parts of the body, so including this limitation allows for all of the possible related images to be shown. Therefore, this would have been obvious to one of ordinary skill in the art.
Regarding claim 14, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the natural-language analysis includes morphological analysis of decomposing each sentence of the series of sentences into words and syntactic analysis of analyzing relationships between the words ("The natural language processing unit 369 is a processing unit which analyzes medical texts. The natural language processing unit 369 has an analyzing unit 370 as a processing unit which analyzes texts. The analyzing unit 370 performs morphological analysis to obtain terms used in texts on a word basis and syntax analysis to analyze the modification relations between words. Morphological analysis is analysis processing for obtaining the original notations of words such as original or basic forms by dividing character strings in texts, classifying the words into part of speech, and removing conjugation, inflection, and the like. This analyzes a text into the form of word strings," Sohma para [0092] and Sohma para [0103]).
Regarding claim 15, Sohma, in view of Kubo, discloses all of the limitations of claim 1. Sohma further discloses wherein the natural-language analysis includes morphological analysis of decomposing each of the series of sentences into words and syntactic analysis of analyzing relationships between the words ("The natural language processing unit 369 is a processing unit which analyzes medical texts. The natural language processing unit 369 has an analyzing unit 370 as a processing unit which analyzes texts. The analyzing unit 370 performs morphological analysis to obtain terms used in texts on a word basis and syntax analysis to analyze the modification relations between words. Morphological analysis is analysis processing for obtaining the original notations of words such as original or basic forms by dividing character strings in texts, classifying the words into part of speech, and removing conjugation, inflection, and the like. This analyzes a text into the form of word strings," Sohma para [0092] and Sohma para [0103]) and building a syntax tree illustrating a structure of dependencies between the words (“Syntax analysis converts the word string into a form such as a tree structure (syntax tree) of words based on the syntax or a modification network structure (modification relation),” Sohma para [0092]),
and wherein the at least one processor extracts the two or more words included in the word strings based on the structure of dependencies between the words ("The natural language processing unit 369 is a processing unit which analyzes medical texts. The natural language processing unit 369 has an analyzing unit 370 as a processing unit which analyzes texts. The analyzing unit 370 performs morphological analysis to obtain terms used in texts on a word basis and syntax analysis to analyze the modification relations between words. Morphological analysis is analysis processing for obtaining the original notations of words such as original or basic forms by dividing character strings in texts, classifying the words into part of speech, and removing conjugation, inflection, and the like. This analyzes a text into the form of word strings," Sohma para [0092], Sohma para [0103], and Sohma Fig. 5B and 6A show the extracted words).
Conclusion
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.
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/ADAM MICHAEL WEAVER/ Examiner, Art Unit 2658
/RICHEMOND DORVIL/ Supervisory Patent Examiner, Art Unit 2658
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