Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/02/2025, 02/20/2026 and 06/05/2026 are being considered by the examiner.
Drawings
The drawings filed on: 08/30/2024 are accepted.
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, 2, 5-11, 14-16 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more
101 Analysis – Claim 1.
The claim is directed to a method, which is a statutory category.
Step 2A – Prong 1 Analysis
Claim 1 recites the following limitations (of which bolded limitations constitute a ‘mental process’ that covers performance of the limitations in the human mind).
A method comprising: receiving a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image; generating, from the first image series, study display layouts for display in a graphical user interface of a display device, the study display layouts including a first display layout and a last display layout; displaying the first display layout in the graphical user interface; receiving a user input to advance to a next display layout; displaying the last display layout in the graphical user interface; receiving a further user input to advance to a next display layout; and determining whether a second data source includes automated image analysis findings for the healthcare study; in an instance where the second data source includes automated image analysis findings for the healthcare study, the method further comprising: generating, from the automated image analysis findings, an automated image analysis display layout for display in the graphical user interface; and displaying the automated image analysis display layout in the graphical user interface on the display device after the displaying of the last display layout of the first image series of the healthcare study; and in an instance where the second data source does not include automated image analysis findings for the healthcare study, the method further comprising: displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study.
As a note, steps that fall within the mental process groupings of abstract ideas because
they cover concepts performed in the human mind, including: observation, evaluation,
judgement and opinion (See MPEP 2106.04(a)(2), subsection III).
With respect to the particular limitations (that were bolded above), these steps can be
practically performed in the human mind using observation, evaluation, judgement
and/or opinion. For example the particular limitations encompass: 1) evaluating whether a second data source includes automated image analysis findings for the healthcare study and making a judgement on when the second source does or does not include automated image analysis findings.
101 Analysis Step 2A, Prong Two
The claim recites the following additional elements:
“receiving a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image”, “receiving a further user input to advance to a next display layout” - these additional elements are considered adding insignificant extra solution activity for mere data gathering. See 2106.05(g) i.e. “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011). The courts have identified these types of elements/limitations are insufficient to integrate the judicial exception into a practical application.
“displaying the first display layout in the graphical user interface; receiving a user input to advance to a next display layout”, “displaying the last display layout in the graphical user interface”, “and displaying the automated image analysis display layout in the graphical user interface on the display device after the displaying of the last display layout of the first image series of the healthcare study”, “displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study” - these additional elements are considered adding insignificant extra solution activity for selecting a particular data source or type of data to be manipulated. See “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)”. The courts have identified these types of elements/limitations are insufficient to integrate the judicial exception into a practical application.
““generating, from the first image series, study display layouts for display in a graphical user interface of a display device, the study display layouts including a first display layout and a last display layout”, “generating, from the automated image analysis findings, an automated image analysis display layout for display in the graphical user interface” – these additional elements are considered merely reciting the words ‘apply it’ with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The courts have identified these types of elements/limitations as insufficient to integrate the judicial exception into a practical application.
101 Analysis Step 2B:
The claim recites the following additional elements:
“receiving a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image”, “receiving a further user input to advance to a next display layout” - these additional elements as explained above, are considered adding insignificant extra solution activity for mere data gathering. See 2106.05(g) i.e. “iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011). The courts have identified these types of elements to be insufficient to qualify as ‘significantly more’ when recited in a claim with a judicial exception.
“displaying the first display layout in the graphical user interface; receiving a user input to advance to a next display layout”, “displaying the last display layout in the graphical user interface”, “and displaying the automated image analysis display layout in the graphical user interface on the display device after the displaying of the last display layout of the first image series of the healthcare study”, “displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study” - these additional elements as explained above, are considered adding insignificant extra solution activity for selecting a particular data source or type of data to be manipulated. See “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)”. The courts have identified these types of elements to be insufficient to qualify as ‘significantly more’ when recited in a claim with a judicial exception.
““generating, from the first image series, study display layouts for display in a graphical user interface of a display device, the study display layouts including a first display layout and a last display layout”, “generating, from the automated image analysis findings, an automated image analysis display layout for display in the graphical user interface” – these additional elements as explained above, are considered merely reciting the words ‘apply it’ with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The courts have identified these types of elements to be insufficient to qualify as ‘significantly more’ when recited in a claim with a judicial exception.
101 Analysis for claims 2 and 5-9
Dependent claims 2 and 5-9, do not recite any further limitations that cause the
claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed
toward additional aspects of the judicial exception. Additional elements such as the
following do not integrate the judicial exception into a practical application, nor do they amount to significantly more when recited in a claim with a judicial exception: “receiving the automated image analysis findings …”, “generating at least … “, “the notification is displayed …”, “the automated image analysis display layout includes/comprises …”, as they are either directed to insignificant extra solution activity of data collection/manipulation/selection or applying the exception using a computer as a tool to perform an abstract idea.
101 Analysis for claim 10
With regards to claim 10, it is rejected under similar rationale as claim 1. It is noted that it additionally recites additional elements of “a network communication interface to receive healthcare studies; a memory coupled to the network communication interface to store received healthcare studies; a display device coupled to the memory to display the received healthcare studies; and one or more processors coupled to the network communication interface, the memory, and the display screen and configured to: …”, These elements are interpreted as merely reciting the words ‘apply it’ with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (discussed in MPEP § 2106.05(f)). As also noted in claim 1, the actions of sending/receiving data are interpreted as insignificant extra solution activity. The courts have identified these types of elements to be insufficient to integrate the judicial exception into a practical application and also the courts have deemed these additional elements to be insufficient to qualify as ‘significantly more’ when recited in a claim with a judicial exception.
101 Analysis for Claims 11 and 14
Dependent claims 11 and 14, do not recite any further limitations that cause the
claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed
toward additional aspects of the judicial exception. Additional elements such as the
following do not integrate the judicial exception into a practical application, nor do they amount to significantly more when recited in a claim with a judicial exception: “receive the automated image analysis findings …”, “… generate the automated analysis display layout …”, as they are either directed to insignificant extra solution activity of data collection/manipulation/selection or applying the exception using a computer as a tool to perform an abstract idea.
101 Analysis for claim 15
With regards to claim 15, it is rejected under similar rationale as claim 1. It is noted that it additionally recites additional elements of “Non-transitory computer-readable storage media having instructions stored thereupon, which, when executed by a system having at least one processor, a memory, and a display device therein, cause the system to perform …”. These elements are interpreted as merely reciting the words ‘apply it’ with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (discussed in MPEP § 2106.05(f)). The courts have identified these types of elements to be insufficient to integrate the judicial exception into a practical application and also the courts have deemed these additional elements to be insufficient to qualify as ‘significantly more’ when recited in a claim with a judicial exception.
101 Analysis for claims 16 and 19-20
Dependent claims 16 and 19-20 do not recite any further limitations that cause the
claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed
toward additional aspects of the judicial exception. Additional elements such as the
following do not integrate the judicial exception into a practical application, nor do they amount to significantly more when recited in a claim with a judicial exception: “receiving the automated image analysis findings …”, “generating the automated image analysis display layout ….”, “the automated image analysis display layout includes ….”., as they are either directed to insignificant extra solution activity of data collection/manipulation/selection or applying the exception using a computer as a tool to perform an abstract idea.
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) 1-4, 6- 7, 9-13, 15-18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fogliato et al (“Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging”, published: 2022, pages 1362-1374) in view of Bernard et al (US Patent: 10140421, issued: Nov. 27, 2018, filed: Jun. 20, 2017) in view of Nakamura (US Application: US 2019/0005354, published: Jan. 3, 2019, filed: Jun. 18, 2018).
With regards to claim 1, Fogliato et al teaches a method comprising:
receiving a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image (page 1365: a series of images are provided (interpreted as images of a healthcare study) to participants );
generating, from the first image series, study display layouts for display in a graphical user interface of a display device, the study display layouts including a first display layout and a last display layout (page 1365: each participants views a display having a layout that includes control(s) for participant to review each image (images cannot be skipped so all images from first to last are viewed /reviewed);
displaying the first display layout in the graphical user interface (page 1365: a first display layout is for participants that are in a two -step workflow (which means the participants are asked to make view and make diagnosis of the image(s) before viewing automated image analysis (from AI inferences) );
receiving a user input to advance to a next display layout (page 1365: each participant in the two step workflow can advance to a next image/frame of the sequence of images for diagnosis/review);
displaying the last display layout in the graphical user interface (page 1365: each participant views a last display of the images in the study (since all participants cannot skip any of the images in the study));
… determining whether a second data source includes automated image analysis findings for the healthcare study (page 1365: a second source of automated analysis findings are determined for display for participants in the two step workflow study via a button to enable display of the automated analysis findings);
in an instance where the second data source includes automated image analysis findings for the healthcare study, the method further comprising: generating, from the automated image analysis findings, an automated image analysis display layout for display in the graphical user interface (page 1365, included automated analysis findings from AI inferences are generated and augmented/overlaid on the interface screen as metadata , flags (indicators) , and/or names of findings and displayed); and
displaying the automated image analysis display layout in the graphical user interface on the display device …(page 1365, included automated analysis findings from AI inferences are generated and augmented/overlaid on the interface screen as metadata and/or names of findings and displayed)
However, Fogliato et al does not teach receiving a further user input to advance to a next display layout; and displaying the automated image analysis display layout … after the displaying of the last display layout of the first image series of the healthcare study; and in an instance where the second data source does not include automated image analysis findings for the healthcare study, the method further comprising: displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study.
Yet Bernard et al teaches receiving a further user input to advance to a next display layout; displaying the automated image analysis display layout … after the displaying of the last display layout of the first image series of the healthcare study (Fig. 1, column 2, lines 1-67, column 3, lines 45-61, column 6, lines 30-49, column 30, lines 42-65: in a networked system having a client computer with a processor and memory, a user traverses and displays all medical scan images for review (blind review) first, and only then subsequently provide input to view automatically annotated data received from a second source. The automatically annotated data is generated/revealed by combining the annotated data with the image regions of the user’s own review/study in a display ).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have modified Fogliato et al’s ability to implement a system that allows users to review a series of images, such that the system is implemented in a networked computer hardware environment and automated image analysis data is displayed after a user performs a review, as taught by Bernard et al. The combination would have allowed Fogliato et al to have allowed for a blind unbiased review before later electing to view annotated abnormalities (Bernard et al, column 25, lines 20-35).
However, although Fogliato et al and Bernard et al teaches distinctly separating viewing and review of manual image analysis and automated image analysis findings, the combination does not expressly teach and in an instance where the second data source does not include automated image analysis findings for the healthcare study, the method further comprising: displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study.
Yet Nakamura teaches and in an instance where the second data source does not include automated image analysis findings for the healthcare study, the method further comprising: displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study (paragraph 0072: Nakamura teaches it is well known to display a message of ‘unavailable’ if comparison image(s) are not available).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have modified Fogliato and Bernard et al’s ability to allow a user to separately view images and paired comparison findings (from the automated image analysis images) such that the comparison findings are displayed after display of last display layout, such that when comparison data is referenced, a message would be displayed indicating lack of paired comparison data, as taught by Nakamura. The combination would have allowed Fogliato and Bernard et al to have reduced user confusion/frustration through provision of information that explains an application state ( when is data is found to be not available).
With regards to claim 2. The method of claim 1, the combination of Fogliato et al, Bernard et al and Nakamura teaches further comprising: receiving the automated image analysis findings for the healthcare study from the second data source, as similarly explained in the rejection of claim 1 (Bernard et al was explained in Fig. 1, column 2, lines 1-67, column 6, lines 30-49, column 30, lines 42-67, column 31, lines 1-6 to teach that in a networked system, a user initiate/display all medical scan images for review (blind review), and then subsequently, annotated data received from a second source is generated/revealed for display), and is rejected under similar rationale.
With regards to claim 3. The method of claim 2, the combination of Fogliato et al, Bernard et al and Nakamura teaches further comprising: generating at least one automated image analysis finding indicator from the automated image analysis findings, wherein the automated image analysis display layout further comprises: at least one of the study display layouts overlaid with the at least one automated image analysis finding indicator, as similarly explained in the rejection of claim 1 (Fig. 1, column 2, lines 1-67, column 6, lines 30-49, column 30, lines 42-65: in a networked system, a user initiate/display all medical scan images for review (blind review), then subsequently, automatically annotated data received from a second source is generated/revealed by combining the annotated data with the image regions of the user’s own review/study in a display ), and is rejected under similar rationale.
With regards to claim 4. The method of claim 2, Fogliato et al teaches wherein generating the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings further comprises: determining images of the first image series based on the automated image analysis findings; generating at least one automated image analysis finding indicator from the automated image analysis findings for each image of the first image series that has automated image analysis findings; and combining the generated automated image analysis finding indicators with the respective images of the first image series to generate images for the automated image analysis display layout, as similarly explained in the rejection of claim 1 (page 1365, included automated analysis findings from AI inferences are generated and augmented/overlaid on the interface screen as metadata , flags (indicators) , and/or names of findings and displayed), and is rejected under similar rationale.
With regards to claim 6. The method of claim 1, Fogliato et al teaches wherein the automated image analysis display layout includes at least one image of the first image series of the healthcare study, as similarly explained in the rejection of claim 1 (page 1365, one or more images from a series of images are displayed), and is rejected under similar rationale.
With regards to claim 7. The method of claim 1, the combination of Fogliato et al, Bernard et al and Nakamura teaches “wherein the notification is displayed after the displaying of the last display layout”, as similarly explained in the rejection of claim 1, and is rejected under similar rationale.
With regards to claim 9. The method of claim 1, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein the images of the first image series, as similarly explained in the rejection of claim 1, and is rejected under similar rationale.
However the combination does not teach the images… are mammography images
Yet Bernard et al further teaches the images… are mammography images
(Fig. 10P, Fig. 10Q: multiple images related to mammography are displayed).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have modified the combination of Fogliato et al, Bernard et al and Nakamura’s ability to present a series of images for review, such that the images for review could have been mammography images, as also taught by Bernard et al. The combination would have allowed Fogliato et al and Bernard et al to have allowed support for review of images in a specific diagnostic area.
With regards to claim 10, the combination of Fogliato et al, Bernard et al and Nakamura teaches a medical image management system comprising: a network communication interface to receive healthcare studies; a memory coupled to the network communication interface to store received healthcare studies; a display device coupled to the memory to display the received healthcare studies; and one or more processors coupled to the network communication interface, the memory, and the display screen and configured to: receive a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image; generate, from the first image series, study display layouts for display in a graphical user interface of the display device, the study display layouts including a first display layout and a last display layout; display the first display layout in the graphical user interface; receive a user input to advance to a next display layout; display the last display layout in the graphical user interface; receive a further user input to advance to a next display layout; determine whether a second data source includes automated image analysis findings for the healthcare study; in an instance where the second data source includes automated image analysis findings for the healthcare study: generate an automated image analysis display layout for display in the graphical user interface from the automated image analysis findings; and display the automated image analysis display layout in the graphical user interface on the display device after the displaying of the last display layout of the first image series of the healthcare study; and in an instance where the second data source does not include automated image analysis findings for the healthcare study: display a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study, as similarly explained in the rejection of claim 1, and is rejected under similar rationale.
With regards to claim 11. The medical image management system of claim 10, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein the one or more processors are further configured to: receive the automated image analysis findings for the healthcare study from the second data source, as similarly explained in the rejection of claim 2, and is rejected under similar rationale.
With regards to claim 12. The medical image management system of claim 11, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein the one or more processors are further configured to: generate at least one automated image analysis finding indicator from the automated image analysis findings, wherein the automated image analysis display layout further comprises: at least one of the study display layouts overlaid with the at least one automated image analysis finding indicator, as similarly explained in the rejection of claim 3, and is rejected under similar rationale.
With regards to claim 13. The medical image management system of claim 10, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein the one or more processors configured to generate the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings are further configured to: determine images of the first image series with automated image analysis findings; generate at least one automated image analysis finding indicator from the automated image analysis findings for each image of the first image series that has automated image analysis findings; and combine the generated automated image analysis finding indicators with the respective images of the first image series to generate images for the automated image analysis display layout, as similarly explained in the rejection of claim 4, and is rejected under similar rationale.
With regards to claim 15, the combination of Fogliato et al, Bernard et al and Nakamura teaches a non-transitory computer-readable storage media having instructions stored thereupon, which, when executed by a system having at least one processor, a memory, and a display device therein, cause the system to perform a method comprising: receiving a healthcare study from a first data source, the healthcare study having a first image series that includes more than one image; generating, from the first image series, study display layouts for display in a graphical user interface of the display device, the study display layouts including a first display layout and a last display layout; displaying the first display layout in the graphical user interface; receiving a user input to advance to a next display layout; displaying the last display layout in the graphical user interface; receiving a further user input to advance to a next display layout; and determining whether a second data source includes automated image analysis findings for the healthcare study; in an instance where the second data source includes automated image analysis findings for the healthcare study, the method further comprising: generating, from the automated image analysis findings, an automated image analysis display layout for display in the graphical user interface; and displaying the automated image analysis display layout in the graphical user interface on the display device after the displaying of the last display layout of the first image series of the healthcare study; and in an instance where the second data source does not include automated image analysis findings for the healthcare study, the method further comprising: displaying a notification to a user in the graphical user interface that indicates that there are no automated image analysis findings for the healthcare study, as similarly explained in the rejection of claim 1, and is rejected under similar rationale.
With regards to claim 16. The non-transitory computer-readable storage media of claim 15, the combination of Fogliato et al, Bernard et al and Nakamura teaches further comprising: receiving the automated image analysis findings for the healthcare study from the second data source, as similarly explained in the rejection of claim 2, and is rejected under similar rationale.
With regards to claim 17. The non-transitory computer-readable storage media of claim 16, the combination of Fogliato et al, Bernard et al and Nakamura teaches further comprising: generating at least one automated image analysis finding indicator from the automated image analysis findings, wherein the automated image analysis display layout further comprises: at least one of the study display layouts overlaid with the at least one automated image analysis finding indicator, as similarly explained in the rejection of claim 3, and is rejected under similar rationale.
With regards to claim 18. The non-transitory computer-readable storage media of claim 15, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein generating the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings further comprises: determining images of the first image series with automated image analysis findings; generating at least one automated image analysis finding indicator from the automated image analysis findings for each image of the first image series that has automated image analysis findings; and combining the generated automated image analysis finding indicators with the respective images of the first image series to generate images for the automated image analysis display layout, as similarly explained in the rejection of claim 4, and is rejected under similar rationale.
With regards to claim 20. The non-transitory computer-readable storage media of claim 15, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein the automated image analysis display layout includes at least one image of the first image series of the healthcare study, as similarly explained in the rejection of claim 6, and is rejected under similar rationale.
Claim(s) 5, 8, 14, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fogliato et al (“Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging”, published: 2022, pages 1362-1374) in view of Bernard et al (US Patent: 10140421, issued: Nov. 27, 2018, filed: Jun. 20, 2017) in view of Nakamura (US Application: US 2019/0005354, published: Jan. 3, 2019, filed: Jun. 18, 2018) in view of Paik et al (US Application: US 2021/0216822, published: Jul. 15, 2021, filed: Jan. 7, 2021).
With regards to claim 5. The method of claim 4, the combination of Fogliato et al, Bernard et al and Nakamura teaches wherein generating the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings, as similarly explained in the rejection of claim 1, and is rejected under similar rationale.
However the combination does not teach “including copies of images of the first image series that do not have automated image analysis findings in the automated image analysis display layout”.
Yet Paik et al teaches including copies of images of the first image series that do not have automated image analysis findings in the automated image analysis display layout (Fig 5: automated image analysis is displayed in a configurable layout for which additional images of a series are displayed that have not been annotated with automated image analysis findings).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have modified Fogliato et al , Bernard et al and Nakamura’s ability to display a first image series and then allow for viewing of automated image analysis findings afterwards, such that the findings could be presented with the paired copies of image series, as taught by Paik et al. The combination would have allowed the user to have understood the context for which the findings have been determined/presented.
With regards to claim 8. The method of claim 1, the combination of Fogliato et al, Bernard et al and Nakamura were explained in the rejection of claim 1 to teach wherein the automated image analysis display layout, and is rejected under similar rationale.
However the combination in claim 1 did not expressly address “ comprises a plurality of automated image analysis display layouts”.
Yet Paik et al further teaches “ comprises a plurality of automated image analysis display layouts” (Fig. 5, paragraph 00138: as shown a plurality of images are laid out having automated AI findings , which allows a user to opt to change/navigate the displayed layouts using multiple modes of navigation).
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have modified the combination of Fogliato et al, Bernard et al and Nakamura’s ability to display an automated image analysis display layout, such that the layout can be configurable to display in a plurality of ways based upon different navigation , while supporting different images, as taught by Paik et al. The combination would have allowed efficient interpretation of images and entry of findings into a medical report (Paik et al, paragraph 0002).
With regards to claim 14. The medical image management system of claim 13, the combination of Fogliato et al, Bernard et al, Nakamura and Paik teaches wherein the one or more processors configured to generate the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings are further configured to: include copies of images of the first image series that do not have automated image analysis findings in the automated image analysis display layout, as similarly explained in the rejection of claim 5, and is rejected under similar rationale.
With regards to claim 19. The non-transitory computer-readable storage media of claim 18, the combination of Fogliato et al, Bernard et al, Nakamura and Paik teaches wherein generating the automated image analysis display layout for display in the graphical user interface from the automated image analysis findings further comprises: including copies of images of the first image series that do not have automated image analysis findings in the automated image analysis display layout, as similarly explained in the rejection of claim 5, and is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Rao et al (US Application: US 2022/0253592): This reference teaches an annotation system used to gather annotations of medical scans based on review of scan image data by users of a system.
Reicher (US Application: US 2018/0075188): This reference teaches a system that reduces anchoring bias by presenting clinical history data only after review of medical images.
Sommer et al (US Application: US 2023/0326598): This reference teaches linking medical image data elements to unique identifiers of one or more contents of report findings.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILSON W TSUI whose telephone number is (571)272-7596. The examiner can normally be reached Monday - Friday 9 am -6 pm.
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/WILSON W TSUI/Primary Examiner, Art Unit 2172
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