DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed April 22, 2026 has been entered. Claims 1, 3-4, and 6-21 remain pending in the application. Applicant’s amendments to the Specification, Drawings, and Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed January 22, 2026, or otherwise, the objections have been withdrawn.
Response to Arguments
Applicant’s arguments, see pages 15-18 of Remarks, filed April 22, 2026, with respect to claim rejections under 35 USC 101 have been fully considered and are persuasive. The 35 USC 101 rejections of claims 1-6, 9-14, and 20-21 from Non-Final Office Action mailed January 22, 2026 have been withdrawn.
Applicant's arguments, see pages 19-21 of Remarks, filed April 22, 2026, regarding the 35 USC 102 rejections of claims 1 and 5, have been fully considered but they are not persuasive.
The applicant argues that the selected algorithm of Weese used in the rejection of claim 1
(Page 8 lines 17-25 and 29-31 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses…The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system”; Note: an algorithm is selected from a memory that stores algorithms, which is equivalent to the repository)
conflicts with the analytic algorithms of Weese used in the rejection of claim 5
(Page 7 lines 15-17, Page 9 lines 19-21 – “to detect anatomies in the image, a mesh based image segmentation method may be used. Each organ may be modeled by a mesh model depicting the surface model of the organ.…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image”; Note: selected algorithms can include analytic algorithms that segment organs or calculate metrics for anomalies like lesions)
because the selected algorithm used in the rejection of claim 1 is associated with a set of diagnoses, while the selected analytical algorithms used in the rejection of claim 5 are used pre-diagnosis. However, in Weese, the selected algorithms are stored in association with a set of possible diagnoses, meaning that the algorithms are intended to be used pre-diagnosis (Page 2 lines 29-34 – “The system also comprises a second unit configured to retrieve a set of selected image-processing
algorithms that are customized for the found set of possible diagnoses and sample cases, and process the region of interest in the acquired image using at least one image-processing algorithm of the set of selected image-processing algorithms, resulting in a confidence measure for each possible diagnosis of the found set of possible diagnoses and sample cases”) or to confirm diagnosis (Page 8 lines 29-34 – “The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system. Accordingly, for each sample case in the medical encyclopedia there is provided at least one selected image-processing algorithm applicable to the region of interest of the image that may be used to confirm diagnosis of such a case within the image”). Furthermore, the following quote conveys how possible diagnoses are found using a search query and how algorithms corresponding to those found diagnoses are retrieved to determine the confidence of each possible diagnosis, once again demonstrating use of the selected algorithm pre-diagnosis despite an association with diagnoses (Page 3 lines 7-17 – “The computer program comprises a first retrieve code segment for retrieving a user defined region of interest in an acquired image to be analyzed, a search code segment for searching a medical database 10 comprising with records describing pathologies using a search query based on information of the region of interest, resulting in a set of possible diagnoses and sample cases, a second retrieve code segment for retrieving a set of selected image-processing algorithms that are customized for the found set of possible diagnoses and sample cases, a process code segment for processing the region of interest in the acquired image using at least one image-processing algorithm of the set of selected image-processing algorithms, resulting in a confidence measure for each possible diagnosis in the found set of possible diagnoses and sample cases”). Therefore, the selected algorithm used in the rejection of claim 1 and the selected analytical algorithm used in the rejection of claim 5 are not conflicting, as they refer to the same selected algorithms that are associated with a set of possible diagnoses and are executed pre-diagnosis.
Claim Objections
Claim 7 is objected to because of the following informalities: Claim 7 is dependent on claim 5, but claim 5 was canceled. Perhaps claim 7 should be dependent on claim 1 or claim 6. Additionally, claim 7 recites the limitation “the visualization algorithm” in line 2-3. There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-4, 6, 8-9, and 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Weese et al. (WO 2009060355 A1) in view of Samset et al. (US 20190392944 A1), hereinafter Weese and Samset respectively.
Regarding claim 1, Weese teaches a system for processing medical image data regarding a clinical question (Page 5 lines 26-29 – “a system 10 for facilitating diagnosis is provided. The system 10 may comprise a medical database 11 comprising pictorial and/or textual information regarding pathological or healthy states, such as sample images or guidance texts for facilitating diagnosis of a disease or disorder of a patient”; Note: diagnosis is a type of clinical question), comprising:
a processor subsystem (Page 5 line 30 – “the system comprises a first processor unit 12 configured to…”) configured:
to determine a use case regarding the clinical question for a patient based on a user input (Page 7 lines 23-30 – “The system further comprises a query unit 14 configured to prepare or retrieve a search query, such as a search mask, that may be used to search the medical database. In 25 Fig. 3e a search query is defined. The query unit may be a part of graphical user interface allowing the user to indicate or refine the search space, such as for example, search diagnosis exhibiting hypointense signals in the left cerebral hemisphere. The query may e.g. from the user's point of view, look like "search cases that contain hypointense to white matter in the left cerebral hemisphere". In an embodiment the search query may comprise textual input from the user”; Note: the user’s input and search query are the use case. The user is the patient);
to retrieve patient data of the patient regarding the use case (Page 8 lines 4-5 – “The client workstation may also be configured to access a patient image e.g. from a scanner or via Picture archiving and communication system (PACS).”; Note: patient images are a type of patient data);
to determine an anatomical object based on the use case, the patient data (Page 10 lines 18-20 – “the graphical user interface is configured to enable the user to indicate which anatomy in the acquired patient image that is of interest, e.g. "left 20 cerebral hemisphere", "midbrain", etc. versus "cerebral hemisphere" only”; Note: the anatomical structure is determined based on patient image data and user input/selection, which is part of the use case), and medical information (Page 6 lines 2-4 – “In Fig. 3d the first processor unit has identified the left and right cerebral hemispheres as an anatomical structure. In Fig. 3e the first processor unit has identified the left cerebral hemisphere as an anatomical structure to be queried”; Note: an anatomical object is determined. It is implied that the anatomical object is determined based on medical information because it could not be identified without knowledge of what the anatomical object looks like);
to select an algorithm from a repository (Page 8 lines 17-25 and 29-31 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses…The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system”; Note: an algorithm is selected from a memory that stores algorithms, which is equivalent to the repository) based on the determined anatomical object and the medical information (Page 8 lines 17-25 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses”; Note: an algorithm is selected based on a specific organ and medical information, including a set of diagnoses and sample cases), wherein the processor subsystem is configured to select the algorithm from the repository containing analytic algorithms for calculating metrics, detection, characterization or segmentation of an anomaly, a tumor and/or an anatomical structure (Page 7 lines 15-17, Page 9 lines 19-21 – “to detect anatomies in the image, a mesh based image segmentation method may be used. Each organ may be modeled by a mesh model depicting the surface model of the organ.…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image”; Note: selected algorithms can include analytic algorithms that segment organs or calculate metrics for anomalies like lesions);
to retrieve image data of the patient (Page 8 lines 4-5 – “The client workstation may also be configured to access a patient image e.g. from a scanner or via Picture archiving and communication system (PACS)”);
and to execute the algorithm on the image data to provide output data for assessing the clinical question (Page 9 lines 6-9 and 19-21, Page 11 lines 1-2 – “the second processor 15 may further be configured to process (15b) the region of interest in the image using the retrieved selected image-processing algorithms to determine at least one diagnosis of the image…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image…the graphical user interface may be visualized on a display for presenting processed information, such as determined diagnoses, etc. to a user”; Note: the selected algorithm is used on the image to output a diagnosis).
Weese does not teach retrieving codified clinical guidelines regarding the use case; nor the “codified clinical guidelines” in the limitation: “to determine an anatomical object based on the use case, the patient data, and the codified clinical guidelines; to select an algorithm from a repository based on the determined anatomical object and the codified clinical guidelines”. However, Samset teaches retrieving codified clinical guidelines regarding the use case (Paragraph 0035 – “the clinical workflow may inform virtual diagnostic assistant 139 of the potential clinical findings to generate, and virtual diagnostic assistant 139 may identify clinical findings by comparing the clinical parameters generated by virtual parameter assistant 138 to various guidelines, which may include normal ranges of the clinical parameters obtained from published guidelines, research studies, etc. In some examples, the normal ranges for the clinical parameters may be adjusted based on patient information (e.g., patient gender, patient age). In other examples, virtual diagnostic assistant 139 may be trained to generate only specific findings for specific patients (e.g., virtual diagnostic assistant 139 may be trained to only generate clinical findings for echocardiograms of adult men)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Samset to retrieve clinical guidelines for the use case because it can assist in quickly determining a diagnosis. “By starting with a set of automatically-generated clinical findings and working backwards to the medical images, the process of reviewing a diagnostic imaging exam may be expedited and aspects of the exam prone to error or inconsistencies (e.g., human-to-human variability in taking measurements of features of the images) may be performed in a uniform manner” (Samset: Paragraph 0004). Additionally, because Weese teaches determining said anatomical object (Page 6 lines 2-4 – “In Fig. 3d the first processor unit has identified the left and right cerebral hemispheres as an anatomical structure. In Fig. 3e the first processor unit has identified the left cerebral hemisphere as an anatomical structure to be queried”; Note: an anatomical object is determined. It is implied that the anatomical object is determined based on medical information because it could not be identified without knowledge of what the anatomical object looks like), and selecting said algorithm, also based on medical information (Page 8 lines 17-25 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses”; Note: an algorithm is selected based on medical information, including a set of possible diagnoses and sample cases), a person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the medical information of Weese could have been substituted for the clinical guidelines of Samset because clinical guidelines are a type of medical information, and both the medical information and clinical guidelines serve the purpose of informing and contributing to medical decisions. Furthermore, a person of ordinary skill in the art would have been able to carry out the substitution. Finally, the substitution achieves the predictable result of determining an anatomical object and algorithm based on the clinical guidelines. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the medical information of Weese for the clinical guidelines of Samset according to known methods to yield the predictable result of determining an anatomical object and algorithm based on the clinical guidelines.
Regarding claim 3, Weese in view of Samset teaches the system according to claim 1. Weese does not teach wherein the codified clinical guidelines for a use case define at least one of: anatomical object; metrics regarding relationships between anatomical objects; criteria regarding boundary values of the metrics; or guidance regarding clinical recommendations based on evaluation of the criteria. However, Samset teaches wherein the codified clinical guidelines for a use case define at least one of: anatomical object; metrics regarding relationships between anatomical objects; criteria regarding boundary values of the metrics; or guidance regarding clinical recommendations based on evaluation of the criteria (Paragraph 0035-0036 – “the clinical workflow may inform virtual diagnostic assistant 139 of the potential clinical findings to generate, and virtual diagnostic assistant 139 may identify clinical findings by comparing the clinical parameters generated by virtual parameter assistant 138 to various guidelines, which may include normal ranges of the clinical parameters obtained from published guidelines, research studies, etc… For example, referring to the left ventricle diastolic diameter, virtual diagnostic assistant 139 may compare the measurement of the left ventricle diameter during diastole generated by virtual parameter assistant 138 (e.g., 6.3 cm) to a normal range of left ventricle diastolic diameters for men (e.g., 4.2-5.9 cm) and generate a clinical finding that the left ventricle diastolic diameter is larger than normal”; Note: the clinical guidelines define an anatomical object, which in this case is the ventricle). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Samset to have the clinical guidelines define an anatomical object because it can be used to identify abnormalities in the anatomical object. “By starting with a set of automatically-generated clinical findings and working backwards to the medical images, the process of reviewing a diagnostic imaging exam may be expedited and aspects of the exam prone to error or inconsistencies (e.g., human-to-human variability in taking measurements of features of the images) may be performed in a uniform manner” (Samset: Paragraph 0004).
Regarding claim 4, Weese in view of Samset teaches the system according to claim 3. Weese further teaches wherein the processor subsystem comprises an algorithm matching lookup table for selecting the algorithm from the repository based on at least one of: the determined anatomical object; the use case; the codified clinical guidelines; the metrics; the criteria; or the guidance (Page 3 lines 1-5, page 8 lines 29-31 – “The method comprises selecting (51) an acquired image, identifying (52) an anatomical region in the acquired image, selecting (53) a record in a database corresponding to the anatomical region in the acquired image, executing (54) at least one image-processing algorithm associated with the record on the acquired image…The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system”; Note: while it is not explicitly stated that there is a lookup table, it is implied. There is a database comprising medical records, where the medical records are associated with respective algorithms. In order for the selection unit to pick an algorithm corresponding to a medical record, it is obvious there would be a table to represent the correspondence between the medical record and algorithms).
Regarding claim 6, Weese in view of Samset teaches the system according to claim 1. Weese further teaches wherein the processor subsystem is configured to select the algorithm from the repository containing visualization algorithms for visualization of the output data (Page 7 lines 10-11 and 15-20, Page 17 lines 8-9 – “The first, second or third image-processing algorithm may be model-based image segmentation techniques…to detect anatomies in the image, a mesh based image segmentation method may be used. Each organ may be modeled by a mesh model depicting the surface model of the organ. In case of brain, such mesh model may contain parts like left/right cerebral hemispheres, cerebellum and so on. The mesh model may then be adapted to the volumetric image, after which the anatomical regions in the image are identified…a display for displaying the sample image, acquired image, or results from image processing”; Note: a mesh/model-based algorithm can be selected, which is a type of visualization algorithm since it helps show the anatomical structure and is later displayed to the user).
Regarding claim 8, Weese in view of Samset teaches the system according to claim 1. Weese further teaches wherein the processor subsystem comprises a natural language processing subsystem for determining the anatomical object and/or metrics related to the object based on the use case and the patient data (Page 7 lines 23-27 and 30, Page 8 lines 8-11 – “The system further comprises a query unit 14 configured to prepare or retrieve a search query… The query unit may be a part of graphical user interface allowing the user to indicate or refine the search space, such as for example, search diagnosis exhibiting hypointense signals in the left cerebral hemisphere… the search query may comprise textual input from the user…the search query may be encoded in standard Unified Medical Language System (UMLS), Foundational Model of Anatomy (FMA), or International Classification of Diseases (ICD-10) terms and may be used in search for relevant cases in the medical encyclopedia”; Note: the query unit is a natural language processing subsystem, as it processes text in the natural language into a medical language format. The query unit is used to determine the anatomical object, which in the example is the left cerebral hemisphere), wherein the natural language processing subsystem is configured to process at least one of: clinical guidelines regarding the use case; documents regarding the use case; or documents regarding the clinical question; for identifying anatomical objects or structures, metrics, criteria or guidance relevant for the clinical question (Page 7 lines 23-24 and 30, Page 8 lines 14-15 – “The system further comprises a query unit 14 configured to prepare or retrieve a search query… the search query may comprise textual input from the user…the query unit 14 may be configured to process the search query in the medical encyclopedia, resulting in a set of possible diagnoses and sample cases”; Note: the search query is a document regarding the use case, as it contains text, and it is used to identify diagnoses or sample cases, which are guidance for the clinical question).
Regarding claim 9, Weese in view of Samset teaches the system according to claim 1. Weese further teaches wherein the processor subsystem is configured to determine the use case; based on detecting an anomaly in the medical image data of an area of the body of the patient; and/or based on detecting an anatomical object or structure affected by an anomaly in the medical image data of an area of the body of the patient (Page 5 lines 30-34, Page 6 lines 8-10 – “the system comprises a first processor unit 12 configured to retrieve 12a a user defined region of interest (ROI) on an image of a patient to be analyzed, as is indicated in Fig. 3b. The first processor unit 12 may also be configured to identify 12b a lesion area in the region of interest using a first image-processing algorithm… Knowing the anatomical structure and location will certainly refine the search space of DDx. In this way, the user may indicate the exact 10 15 anatomy of interest, e.g. "find diagnosis that exhibit lesions in the midbrain."”; Note: a lesion, which is an anomaly, is detected in the medical patient image data. Detecting the lesion helps with determining the use case, as it refines the search space); for enabling selecting said algorithm from the repository based on the detected anomaly and/or affected anatomical object or affected structure (Page 3 lines 1-5, Page 5 lines 32-33, Page 6 lines 8-10, Page 9 lines 17-19 – “The method comprises selecting (51) an acquired image, identifying (52) an anatomical region in the acquired image, selecting (53) a record in a database corresponding to the anatomical region in the acquired image, executing (54) at least one image-processing algorithm associated with the record on the acquired image… The first processor unit 12 may also be configured to identify 12b a lesion area in the region of interest using a first image-processing algorithm…Knowing the anatomical structure and location will certainly refine the search space of DDx. In this way, the user may indicate the exact 10 15 anatomy of interest… The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases”; Note: Detecting the lesion allows for finding medical records related to the lesion, and the medical records are associated with algorithms that can be selected and used on the image). Weese does not teach retrieving the codified clinical guidelines. However, Samset teaches retrieving the codified clinical guidelines (Paragraph 0035 – “the clinical workflow may inform virtual diagnostic assistant 139 of the potential clinical findings to generate, and virtual diagnostic assistant 139 may identify clinical findings by comparing the clinical parameters generated by virtual parameter assistant 138 to various guidelines, which may include normal ranges of the clinical parameters obtained from published guidelines, research studies, etc. In some examples, the normal ranges for the clinical parameters may be adjusted based on patient information (e.g., patient gender, patient age). In other examples, virtual diagnostic assistant 139 may be trained to generate only specific findings for specific patients (e.g., virtual diagnostic assistant 139 may be trained to only generate clinical findings for echocardiograms of adult men)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Samset to retrieve clinical guidelines for the use case because it can assist in quickly determining a diagnosis. “By starting with a set of automatically-generated clinical findings and working backwards to the medical images, the process of reviewing a diagnostic imaging exam may be expedited and aspects of the exam prone to error or inconsistencies (e.g., human-to-human variability in taking measurements of features of the images) may be performed in a uniform manner” (Samset: Paragraph 0004).
Regarding claim 20, Weese teaches a computer-implemented method for processing medical image data regarding a clinical question (Page 12 lines 29-30, Page 13 lines 8-9 – “a computer-readable medium having embodied thereon a computer program for processing by a computer is provided…method or computer-readable medium is provided for facilitating diagnosis of a region of interest in an image dataset”), comprising:
determining a use case regarding the clinical question for a patient based on a user input (Page 7 lines 23-30 – “The system further comprises a query unit 14 configured to prepare or retrieve a search query, such as a search mask, that may be used to search the medical database. In 25 Fig. 3e a search query is defined. The query unit may be a part of graphical user interface allowing the user to indicate or refine the search space, such as for example, search diagnosis exhibiting hypointense signals in the left cerebral hemisphere. The query may e.g. from the user's point of view, look like "search cases that contain hypointense to white matter in the left cerebral hemisphere". In an embodiment the search query may comprise textual input from the user”; Note: the user’s input and search query are the use case. The user is the patient);
retrieving patient data of the patient regarding the use case (Page 8 lines 4-5 – “The client workstation may also be configured to access a patient image e.g. from a scanner or via Picture archiving and communication system (PACS).”; Note: patient images are a type of patient data);
determining an anatomical object based on the use case, the patient data (Page 10 lines 18-20 – “the graphical user interface is configured to enable the user to indicate which anatomy in the acquired patient image that is of interest, e.g. "left 20 cerebral hemisphere", "midbrain", etc. versus "cerebral hemisphere" only”; Note: the anatomical structure is determined based on patient image data and user input/selection, which is part of the use case), and medical information (Page 6 lines 2-4 – “In Fig. 3d the first processor unit has identified the left and right cerebral hemispheres as an anatomical structure. In Fig. 3e the first processor unit has identified the left cerebral hemisphere as an anatomical structure to be queried”; Note: an anatomical object is determined. It is implied that the anatomical object is determined based on medical information because it could not be identified without knowledge of what the anatomical object looks like);
selecting an algorithm based on the determined anatomical object (Page 8 lines 17-25 and 29-31 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses”; Note: the selected algorithm corresponds to a specific organ), wherein the algorithm is selected from a repository containing analytic algorithms for calculating metrics, detection, characterization or segmentation of an anomaly, a tumor and/or an anatomical structure (Page 7 lines 15-17, Page 8 lines 29-31, Page 9 lines 19-21 – “to detect anatomies in the image, a mesh based image segmentation method may be used. Each organ may be modeled by a mesh model depicting the surface model of the organ…The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image”; Note: selected algorithms can include analytic algorithms that segment organs or calculate metrics for anomalies like lesions. An algorithm is selected from a memory that stores algorithms, which is equivalent to the repository);
retrieving image data of the patient (Page 8 lines 4-5 – “The client workstation may also be configured to access a patient image e.g. from a scanner or via Picture archiving and communication system (PACS)”);
and executing the algorithm on the image data to provide output data for assessing the clinical question (Page 9 lines 6-9 and 19-21, Page 11 lines 1-2 – “the second processor 15 may further be configured to process (15b) the region of interest in the image using the retrieved selected image-processing algorithms to determine at least one diagnosis of the image…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image…the graphical user interface may be visualized on a display for presenting processed information, such as determined diagnoses, etc. to a user”; Note: the selected algorithm is used on the image to output a diagnosis).
Weese does not teach retrieving codified clinical guidelines regarding the use case; nor the “codified clinical guidelines” in the limitation: “determining an anatomical object based on the use case, the patient data, and the codified clinical guidelines”. However, Samset teaches retrieving codified clinical guidelines regarding the use case (Paragraph 0035 – “the clinical workflow may inform virtual diagnostic assistant 139 of the potential clinical findings to generate, and virtual diagnostic assistant 139 may identify clinical findings by comparing the clinical parameters generated by virtual parameter assistant 138 to various guidelines, which may include normal ranges of the clinical parameters obtained from published guidelines, research studies, etc. In some examples, the normal ranges for the clinical parameters may be adjusted based on patient information (e.g., patient gender, patient age). In other examples, virtual diagnostic assistant 139 may be trained to generate only specific findings for specific patients (e.g., virtual diagnostic assistant 139 may be trained to only generate clinical findings for echocardiograms of adult men)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Samset to retrieve clinical guidelines for the use case because it can assist in quickly determining a diagnosis. “By starting with a set of automatically-generated clinical findings and working backwards to the medical images, the process of reviewing a diagnostic imaging exam may be expedited and aspects of the exam prone to error or inconsistencies (e.g., human-to-human variability in taking measurements of features of the images) may be performed in a uniform manner” (Samset: Paragraph 0004). Additionally, because Weese teaches determining said anatomical object based on medical information (Page 6 lines 2-4 – “In Fig. 3d the first processor unit has identified the left and right cerebral hemispheres as an anatomical structure. In Fig. 3e the first processor unit has identified the left cerebral hemisphere as an anatomical structure to be queried”; Note: an anatomical object is determined. It is implied that the anatomical object is determined based on medical information because it could not be identified without knowledge of what the anatomical object looks like), a person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the medical information of Weese could have been substituted for the clinical guidelines of Samset because clinical guidelines are a type of medical information, and both the medical information and clinical guidelines serve the purpose of informing and contributing to medical decisions. Furthermore, a person of ordinary skill in the art would have been able to carry out the substitution. Finally, the substitution achieves the predictable result of determining an anatomical object based on the clinical guidelines. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the medical information of Weese for the clinical guidelines of Samset according to known methods to yield the predictable result of determining an anatomical object based on the clinical guidelines.
Regarding claim 21, Weese in view of Samset teaches the method according to claim 20. Weese further teaches a non-transitory computer-readable medium comprising instructions for causing a processor system to perform the method (Page 3 lines 6-7, Page 13 lines 16-17 and 24-26 – “a computer-readable medium having embodied thereon a computer program for processing by a processor is provided…The processor unit may be any unit normally used for performing the involved tasks, e.g. a hardware, such as a processor with a memory…The memory may also be a FLASH memory such as a USB, Compact Flash, SmartMedia, MMC 25 memory, MemoryStick, SD Card, MiniSD, MicroSD, xD Card, TransFlash, and MicroDrive memory etc.”; Note: flash memory is a type of non-transitory computer-readable medium).
Claims 7, 15-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Weese in view of Samset and Shukla (US 20110161854 A1), hereinafter Shukla.
Regarding claim 7, Weese in view of Samset teaches the system according to claim 6. Weese does not teach wherein the processor subsystem comprises a layout rendering and interaction manager for selecting the visualization algorithm matching the output data as provided by the analytic algorithm for assessing the clinical question. However, Shukla teaches a layout rendering and interaction manager for selecting the visualization algorithm matching the output data as provided by the analytic algorithm for assessing the clinical question (Paragraph 0027, 0043, 0046 – “By selecting a view and/or indicator of data within a view, a detailed view is generated to convey information regarding diagnosis, treatment, medication, physician specialist, time frame, etc…Each presentation pane can have its different context sensitive graphical user interface ("GUI") controls…Graphical and/or overlay elements of each of presentation panes can be clickable and/or otherwise selectable resulting in a certain action happening upon clicking or selecting an element, thus being a special sort of interactive controls…A user can select a tab 120 for review and access to included information via the manager interface 100.”; Note: the manager interface is equivalent to the layout rendering and interaction manager. A user can select a view/visualization, which will then render/display the corresponding layout of clinical information. The output data provided by the analytic algorithm was previously taught by Weese in the rejection of claim 1).
Regarding claim 15, Weese in view of Samset teaches the system according to claim 1. Weese further teaches wherein the selected algorithm is an analytical algorithm arranged to analyse the image data for generating a 3D anatomical model, anatomical annotations or metrics regarding the anatomical object (Page 7 lines 15-20 – “to detect anatomies in the image, a mesh based image segmentation method may be used. Each organ may be modeled by a mesh model depicting the surface model of the organ. In case of brain, such mesh model may contain parts like left/right cerebral hemispheres, cerebellum and so on. The mesh model may then be adapted to the volumetric image, after which the anatomical regions in the image are identified”; Note: a mesh model of the organ, which is equivalent to a 3D anatomical model, is generated using a mesh-based image segmentation algorithm; the algorithm is analytical). Weese does not teach further comprising a display, wherein the display comprises a 2D view for displaying a guidance panel showing the anatomical annotations, metrics, codified clinical guidelines and/or a slice of the medical image data, and a 3D view for displaying the 3D anatomical model; wherein the processor subsystem is configured to synchronize the 3D view upon user input regarding the 2D view; or to synchronize the 2D view upon user input regarding the 3D view. However, Shukla teaches a display comprising a 2D view for displaying a guidance panel showing the anatomical annotations, metrics, codified clinical guidelines and/or a slice of the medical image data, and a 3D view for displaying the 3D anatomical model (Fig. 1, Paragraph 0047-0048, 0051 – “Views can provide 2D and/or 3D anatomical views based on actual image(s) and/or idealized anatomical representations, for example. Within each view 131-134 (and/or a composite view), one or more indicators 135-139 can be shown indicating medical data associated with the patient. For example, the anatomy representation 131-134 can include a graphical indication of findings and/or other events/conditions for the patient, areas of image data for the patient, and/or other information… The manager 100 also includes one or more additional expandable windows including, for example, one or more of allergies 160, lab results 161, radiology 162, demographics 163, medications 164, problems 165, orders 166, alert review 167, etc.”; Note: Fig. 1 shows a 3D view of a 3D anatomical model of the patient on the left side and a 2D view of textual information guiding the patient on their metrics on the right side; see modified screenshot of Fig. 1 below); wherein the processor subsystem is configured to synchronize the 3D view upon user input regarding the 2D view; or to synchronize the 2D view upon user input regarding the 3D view (Paragraph 0042, 0054 – “Content of the presentation panes can be synchronized between any two or more panes as part of a customization pattern, and/or by explicit choice of an operator, for example. For purposes of example only, selection of an anatomical region (e.g., an abdominal region) on anatomical presentation pane automatically reduces a list of historical exams to only those prior exams targeted to the selected anatomical part… the representation 131-134 can be a 3D representation of a body, certain body part”; Note: the 2D view of the historical exams are synchronized to the selection of an anatomical region on the 3D anatomical structure of the patient. The historical exams are implied to be part of the 2D view, as they are textual information). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla to have a 2D view, in order “to help various end users of the system to explain diagnosis and/or treatment (e.g., between a patient who is visiting a second time and a nurse, between a physician/surgeon and a patient, etc.), explore a solution for a medical procedure (e.g., between two surgeons deciding on a medical procedure), maintain a visual history of a patient's health (e.g., hospital systems), etc.” (Shukla: Paragraph 0028). In other words, a 2D view provides text information to help users understand a medical condition. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla to have a 3D view because “The anatomical system views) can be used as a solution for various end users, such as between a patient and a triage nurse to understand the patient's present health condition, past health history, and pending a health condition which was diagnosed but not treated; for a surgeon to explore multiple medical procedures on a patient 3D visualization; between a surgeon and a patient to explain the related medical procedure which will be conducted on patient; etc. The views) can form a visual part of an enterprise solution system, for example” (Shukla: Paragraph 0024). In other words, a 3D view provides a clear visualization of a patient’s health. Finally, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla top synchronize the 2D and 3D view for the benefit of being able to use the views together, so that they can supplement each other. This would enhance the user experience and increase their understanding of the condition.
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Screenshot of Fig. 1 (taken from Shukla)
Regarding claim 16, Weese in view of Samset and Shukla teaches the system according to claim 15. Weese does not teach wherein the processor subsystem is configured to synchronize a 3D viewpoint with respect to the 3D model upon user interaction in the 2D view comprising one of manipulating a cursor position in a slice; selecting anatomical annotations, the metrics or the codified clinical guidelines in the guidance panel; or to synchronize the 2D view upon change of a 3D cursor position in the 3D view by displaying a slice, anatomical annotations or metrics corresponding to the 3D cursor position. However, Shukla teaches synchronizing a 3D viewpoint with respect to the 3D model upon user interaction in the 2D view comprising one of manipulating a cursor position in a slice; selecting anatomical annotations, the metrics or the codified clinical guidelines in the guidance panel (Fig. 1, Paragraph 0031, 0049 – “Information can be input to update the views and associated data. For example, 3D skeletal analysis information from a 3D digitizer can be input to display a 3D view of the patient's body with different systems identified…For example, the musculature view 131 can include a cataract indicator 135 and a shoulder muscle indicator 136. The skeletal representation 132 can include a collar bone fracture 137 and an osteoarthritis indicator 138. The circulatory view 133 can include a coronary artery blockage indicator 139, for example. By selecting a system view 131-134 and/or an indicator 135-139, a user can drill down or retrieve addition information and/or views”; Note: a user selects an indicator, which is an anatomical annotation as shown in Fig. 1, which retrieves additional 3D views; see screenshot of Fig. 1 above. In other words, the user interaction in the 2D view with the indicator causes a corresponding change in the 3D portion of the display, which is interpreted as synchronization); or synchronizing the 2D view upon change of a 3D cursor position in the 3D view by displaying a slice, anatomical annotations or metrics corresponding to the 3D cursor position (Paragraph 0042, 0054 – “Content of the presentation panes can be synchronized between any two or more panes as part of a customization pattern, and/or by explicit choice of an operator, for example. For purposes of example only, selection of an anatomical region (e.g., an abdominal region) on anatomical presentation pane automatically reduces a list of historical exams to only those prior exams targeted to the selected anatomical part… the representation 131-134 can be a 3D representation of a body, certain body part”; Note: the 2D view of the historical exams are synchronized to the selection of an anatomical region on the 3D anatomical structure of the patient. The historical exams, which are metrics, are implied to be part of the 2D view, as they are textual information). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla top synchronize the 2D and 3D view for the benefit of being able to use the views together, so that they can supplement each other. This would enhance the user experience and increase their understanding of the condition.
Regarding claim 18, Weese in view of Samset and Shukla teaches the system according to claim 15. Weese does not teach wherein the processor subsystem is configured to display the 3D anatomical model while at least one of: removing non-relevant structures from the 3D model based on the use case; making the anatomical object transparent; choosing a viewpoint that shows a suitable angle to evaluate a tumor-vessel contact; making a footprint visible to clarify the area of contact and trajectory length of a tumor-vessel contact; or adapting lighting settings for the 3D model visualization to highlight the tumor- vessel contact. However, Shukla teaches displaying the 3D anatomical model while at least one of: removing non-relevant structures from the 3D model based on the use case; making the anatomical object transparent; choosing a viewpoint that shows a suitable angle to evaluate a tumor-vessel contact; making a footprint visible to clarify the area of contact and trajectory length of a tumor-vessel contact; or adapting lighting settings for the 3D model visualization to highlight the tumor- vessel contact (Fig. 1, Paragraph 0024, 0047 – “Certain examples provide systems and methods to display a three-dimensional (3D) view of the body with different systems shadowed, emphasized, or highlighted. The view can provide a composite shadowed view of all body systems together for a patient and can be used across a treatment timeline, such as a complete duration of a patient's stay in a hospital through various stages. The composite view can be separated into its component anatomical system views (e.g., circulatory, skeletal, organ, etc.), for example. The anatomical system views) can be used as a solution for various end users, such as between a patient and a triage nurse to understand the patient's present health condition…the anatomical views 131-134 can be combined into a single composite view from which the individual body system views 131-134 can be separated or isolated for viewing, for example. The anatomical views include a musculature system view 131, a skeletal system view 132, a circulatory system view 133, and an organ system view 134, for example. Views can provide 2D and/or 3D anatomical views based on actual image(s) and/or idealized anatomical representations”; Note: a 3D anatomical model is displayed and is isolated by the anatomical system based on the patient’s health condition. In other words, only the relevant anatomical system is shown). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla to display the 3D anatomical model with irrelevant structures removed for the benefit of user-friendly viewing options and allowing the user to focus on a specific health problem, which may help with better understanding the condition.
Regarding claim 19, Weese in view of Samset teaches the system according to claim 1. Weese does not teach the system comprising the display having a 2D display for displaying a guidance panel showing anatomical annotations, the metrics, the codified clinical guidelines and/or a slice of the medical image data, and a 3D display for displaying a 3D anatomical model of the anatomical object. However, Shukla teaches the display having a 2D display for displaying a guidance panel showing anatomical annotations, the metrics, the codified clinical guidelines and/or a slice of the medical image data (Fig. 1, Paragraph 0051 – “The manager 100 also includes one or more additional expandable windows including, for example, one or more of allergies 160, lab results 161, radiology 162, demographics 163, medications 164, problems 165, orders 166, alert review 167, etc.”; Note: Fig. 1 shows a 2D view, including 160-169, of textual information guiding the patient on their metrics; see modified screenshot of Fig. 1 above), and a 3D display for displaying a 3D anatomical model of the anatomical object (Fig. 1, Paragraph 0054 – “The anatomic representation(s) 131-134…can be a 3D representation of a body, certain body part, etc.”; Note: Fig. 1 shows a 3D view of a 3D anatomical model of the patient on the left side; see modified screenshot of Fig. 1 above). ). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla to have a 2D view, in order “to help various end users of the system to explain diagnosis and/or treatment (e.g., between a patient who is visiting a second time and a nurse, between a physician/surgeon and a patient, etc.), explore a solution for a medical procedure (e.g., between two surgeons deciding on a medical procedure), maintain a visual history of a patient's health (e.g., hospital systems), etc.” (Shukla: Paragraph 0028). In other words, a 2D view provides text information to help users understand a medical condition. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Shukla to have a 3D view because “The anatomical system views) can be used as a solution for various end users, such as between a patient and a triage nurse to understand the patient's present health condition, past health history, and pending a health condition which was diagnosed but not treated; for a surgeon to explore multiple medical procedures on a patient 3D visualization; between a surgeon and a patient to explain the related medical procedure which will be conducted on patient; etc. The views) can form a visual part of an enterprise solution system, for example” (Shukla: Paragraph 0024). In other words, a 3D view provides a clear visualization of a patient’s health.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Weese in view of Samset and Liang et al. (US 20100316268 A1), hereinafter Liang.
Regarding claim 10, Weese in view of Samset teaches the system according to claim 1. Weese does not teach wherein the use case is treatability based on the relation of a lesion with surrounding anatomical structures; or resectability of tumors in the vicinity of blood vessels. However, Liang teaches wherein the use case is treatability based on the relation of a lesion with surrounding anatomical structures; or resectability of tumors in the vicinity of blood vessels (Paragraph 0005-0006 – “Liver tumor resection can be an efficient treatment method for addressing liver cancer. Before surgery, physicians need to carefully evaluate a hepatic lesion or tumor to be re-sectioned, the volume of the expected remaining liver segments, how a proposed resection is going to affect nearby vascular structures and corresponding blood supply/drainage regions, and how the resection will affect biliary systems… During the planning stage, a surgeon has to understand the spatial relationships between tumors and surrounding vessel structures”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Liang to have the use case be treatability based on the relation of a lesion with surrounding anatomical structures because the relation of a lesion with surrounding anatomical structures can determine if the lesion can be removed or not (Liang: Paragraph 0005-0006), and removing lesions is one of the treatments for cancer. If the use case is related to cancer, then it is important to consider how close the lesion is with nearby structures to avoid removing or damaging healthy cells during treatment.
Claims 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Weese in view of Samset and Verdonck (US 7636460 B2), hereinafter Verdonck.
Regarding claim 11, Weese in view of Samset teaches the system according to claim 1. Weese further teaches wherein the image data comprises three-dimensional (3D) image data (Page 8 lines 4-5, Page 9 lines 18-20, Page 13 lines 27-29 – “The client workstation may also be configured to access a patient image e.g. from a scanner or via Picture archiving and communication system (PACS)… The mesh model may then be adapted to the volumetric image, after which the anatomical regions in the image are identified… the system is comprised in a medical workstation or medical system, such as a Computed Tomography (CT) system, Magnetic Resonance Imaging (MRI) System or Ultrasound Imaging (US) system”; Note: the image data is volumetric image from a CT, MRI, or ultrasound system, which produce 3D images); and the anatomical object is a 3D object in the 3D image data (Page 6 line 35, Page 7 lines 1-2, Page 9 lines 18-20, Page 13 lines 27-29 – “the first processor unit may be configured to identify 12c an anatomical structure in the image…The mesh model may then be adapted to the volumetric image, after which the anatomical regions in the image are identified… the system is comprised in a medical workstation or medical system, such as a Computed Tomography (CT) system, Magnetic Resonance Imaging (MRI) System or Ultrasound Imaging (US) system”; Note: it is implied that the anatomical object is a 3D object since it is part of the 3D image data). Weese does not teach wherein the selected algorithm is a slicing algorithm; and the processor subsystem is configured: to determine an anatomically relevant path via the 3D object; to execute the slicing algorithm on the image data to provide, as display data, slices of the 3D image data that are perpendicular to the anatomically relevant path for assessing the clinical question. However, Verdonck teaches wherein the selected algorithm is a slicing algorithm (Col. 2 lines 33-38 – “according to the method of our invention which is characterized in that, a reference direction is determined in each cross sectional slice, and the object data set is created by concatenating the cross sectional slices, each cross sectional slice orientated so that the reference directions in the cross sectional slices are aligned”; Note: this method is a slicing algorithm. The selection of the algorithm was previously taught by Weese in the rejection of claim 1); and the processor subsystem is configured: to determine an anatomically relevant path via the 3D object (Col. 1 lines 13-17, Col. 4 lines 24-27 – “Medical imaging in particular contains many examples of tortuous objects. Arteries, veins, nerves and the lower digestive tract are all examples of structures which present with a large degree of tortuosity in relation to the surrounding tissue…The curve which constitutes the axis of the tortuous structure is described at all points by a tangent vector which identifies the direction in which the curve moves”; Note: the curve of the tortuous structure is determined. The curve is equivalent to the anatomically relevant path. The tortuous structure, like an artery, is a 3D object); to execute the slicing algorithm on the image data to provide, as display data, slices of the 3D image data that are perpendicular to the anatomically relevant path for assessing the clinical question (Col. 2 lines 34-38, Col. 4 lines 10-17, Col. 7 lines 11-12 – “a reference direction is determined in each cross sectional slice, and the object data set is created by concatenating the cross sectional slices, each cross sectional slice orientated so that the reference directions in the cross sectional slices are aligned…The result of any of these cross sectional sampling methods is a series of such slices, each including a cross section of the tortuous structure which is essentially perpendicular to the slice throughout the length along which it intersects that slice. As long as each cross sectional slice remains centered on the tortuous structure as it is calculated in the object data set, the included section of tortuous structure remains in the center of each cross sectional slice…The method can be easily extended to 3 dimensions”; Note: the slicing algorithm results in slices that are perpendicular to the tortuous structure, which is the anatomically relevant path). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Verdonck to have and execute a slicing algorithm for the benefit of better 3D viewing of complex anatomical structures: “the clear visualization of complex and tortuous structures within a three dimensional object data set is a difficult problem within imaging…if the structure were a branching artery, reference directions might be chosen to produce orientations in the final images in which the branching structure of the artery was rendered particularly clearly” (Verdonck: Col. 1 lines 11-13, Col. 5 lines 63-67). In other words, aligning the cross-sectional slices of the anatomical structure in a specific way, using the slicing algorithm, produces a clearer image of the structure. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Verdonck to determine an anatomically relevant path via the 3D object for the benefit of aligning the cross-sectional slices for optimal viewing. The path contributes to how the slices are aligned.
Regarding claim 12, Weese in view of Samset and Verdonck teaches the system according to claim 11. Weese does not teach wherein the slicing algorithm comprises the steps of: selecting a first position on the anatomically relevant path and extract first 3D coordinates of the first position; selecting a second position on the anatomically relevant path at a distance from the first position and extract second 3D coordinates of the second position; calculating a vector from the first position to the second position; computing a slice passing through the first position at an angle perpendicular to the vector. However, Verdonck teaches selecting a first position on the anatomically relevant path and extract first 3D coordinates of the first position (Col. 7 lines 10-14 – “The Figure shows the method as applied to 2 dimensions. The method can be easily extended to 3 dimensions. A 2 dimensional curve 701 is shown with 2 perpendicular cross sectional slices 702 and 703 crossing the curve at points 704 and 705”; Note: the curve is equivalent to the anatomically relevant path, and the point 704 is equivalent to the first position and first coordinate. The coordinate is 3D because the method is in 3D. See screenshot of Fig. 7 below); selecting a second position on the anatomically relevant path at a distance from the first position and extract second 3D coordinates of the second position (Col. 7 lines 10-14 – “The Figure shows the method as applied to 2 dimensions. The method can be easily extended to 3 dimensions. A 2 dimensional curve 701 is shown with 2 perpendicular cross sectional slices 702 and 703 crossing the curve at points 704 and 705”; Note: the curve is equivalent to the anatomically relevant path, and the point 705 is equivalent to the second position and second coordinate. The coordinate is 3D because the method is in 3D. See screenshot of Fig. 7 below); calculating a vector from the first position to the second position (Col. 7 lines 10-20 – “The Figure shows the method as applied to 2 dimensions. The method can be easily extended to 3 dimensions. A 2 dimensional curve 701 is shown with 2 perpendicular cross sectional slices 702 and 703 crossing the curve at points 704 and 705. A tangent vector can be defined at both these points, vector 706 being the tangent at point 704 on slice 702 and vector 707 being the equivalent at point 705 on slice 703. A representative reference direction 708, a vector, is defined within cross sectional slice 702, originating at point 704 and this is transferred to originate from point 705 in slice 703”; Note: vector 708 is calculated from point 704 to 705); computing a slice passing through the first position at an angle perpendicular to the vector (Col. 7 lines 10-23 – “The Figure shows the method as applied to 2 dimensions. The method can be easily extended to 3 dimensions. A 2 dimensional curve 701 is shown with 2 perpendicular cross sectional slices 702 and 703 crossing the curve at points 704 and 705. A tangent vector can be defined at both these points, vector 706 being the tangent at point 704 on slice 702 and vector 707 being the equivalent at point 705 on slice 703. A representative reference direction 708, a vector, is defined within cross sectional slice 702, originating at point 704 and this is transferred to originate from point 705 in slice 703. Because of the curvature of 701, the vector 708 no longer lies within the slice at 705, viz. 703. A new axis is therefore defined at point 705, being the line perpendicular to the plane containing 707 and point 704”; Note: the plane containing 707 and point 704 is equivalent to the computed slice. It is perpendicular to the vector; see screenshot of Fig. 7 below). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Verdonck to determine an anatomically relevant path by calculating a vector between a first and second position and computing a perpendicular slice because the vector along the path determines the direction the slice should face for alignment, and when this process repeats, it would result in Fig. 1 of Verdonck (shown below), which shows alignment for better viewing of the anatomical structure.
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Screenshot of Fig. 7 (taken from Verdonck)
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Screenshot of Fig. 1 (taken from Verdonck)
Regarding claim 13, Weese in view of Samset and Verdonck teaches the system according to claim 11. Weese futher teaches wherein the processor subsystem is configured: to select an algorithm from the repository for processing medical image data (Page 8 lines 17-25 and 29-31 – “The system may further comprise a second processor unit 15 configured to retrieve (15a) a set of selected image-processing algorithms that are associated with the found set of diagnoses and sample cases, and optionally located on a memory 16 or a selection unit 20. A selected image-processing algorithm may be an algorithm that may be customized from a common IP algorithm and may be adapted to the modality, to the organ and so on. By customized is here meant that the algorithm may be modified particularly for being used on a certain sample image, and the acquired image resulting in parameters that may be used for facilitating diagnosis, or for discrimination between different diagnoses…The selected image-processing algorithms associated with the set of diagnoses and sample cases, which are located in the medical encyclopedia, may be stored either in the medical encyclopedia or in a memory connected to the system”); to execute the algorithm to calculate clinically relevant information (Page 9 lines 6-9 and 19-21, Page 11 lines 1-2 – “the second processor 15 may further be configured to process (15b) the region of interest in the image using the retrieved selected image-processing algorithms to determine at least one diagnosis of the image…the selected image-processing algorithms is configured to calculate e.g. characteristics of lesion properties such as image appearance, or border characteristics in the image to facilitate subsequent diagnosis of the image…the graphical user interface may be visualized on a display for presenting processed information, such as determined diagnoses, etc. to a user”; Note: the selected algorithm is used on the image to output a diagnosis). Weese does not teach the “2D algorithm” and executing the “2D algorithm on a slice” from the limitations: “wherein the processor subsystem is configured: to select a 2D algorithm from the repository for processing medical image data; to execute the 2D algorithm on a slice to calculate clinically relevant information”. However, Verdonck teaches a 2D algorithm for processing medical image data (Col. 2 lines 33-38, Col. 5 lines 63-67 – “according to the method of our invention which is characterized in that, a reference direction is determined in each cross sectional slice, and the object data set is created by concatenating the cross sectional slices, each cross sectional slice orientated so that the reference directions in the cross sectional slices are aligned…For example, if the structure were a branching artery, reference directions might be chosen to produce orientations in the final images in which the branching structure of the artery was rendered particularly clearly”; Note: this method is a 2D algorithm, as it operates on cross-sectional slices); and executing the 2D algorithm on a slice to calculate clinically relevant information (Col. 2 lines 33-38, Col. 5 lines 63-67 – “according to the method of our invention which is characterized in that, a reference direction is determined in each cross sectional slice, and the object data set is created by concatenating the cross sectional slices, each cross sectional slice orientated so that the reference directions in the cross sectional slices are aligned…For example, if the structure were a branching artery, reference directions might be chosen to produce orientations in the final images in which the branching structure of the artery was rendered particularly clearly”; Note: this method is a 2D algorithm, as it operates on cross-sectional slices. The algorithm helps with rendering anatomical structures, like arteries, which in turn helps with calculating clinical information about the anatomical structure). A person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the algorithm of Weese could have been substituted for the 2D algorithm of Verdonck because both the algorithm and 2D algorithm serve the purpose of processing medical image data. Furthermore, a person of ordinary skill in the art would have been able to carry out the substitution. Finally, the substitution achieves the predictable result of providing medical information based on images. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the algorithm of Weese for the 2D algorithm of Verdonck according to known methods to yield the predictable result of providing medical information based on images.
Claims 14 are rejected under 35 U.S.C. 103 as being unpatentable over Weese in view of Samet, Verdonck, and Gindele et al. (US 20090279756 A1), hereinafter Gindele.
Regarding claim 14, Weese in view of Samset and Verdonck teaches the system according to claim 11. Weese does not teach wherein the anatomically relevant path via the 3D object is determined along an interface of the 3D object and a further anatomical structure. However, Gindele teaches wherein the anatomically relevant path via the 3D object is determined along an interface of the 3D object and a further anatomical structure (Paragraph 0041 – “The image-editing algorithm constructs a cutting plane in 3-dimensional space that includes the edit point 205 shown in FIG. 2. Line 206, shown in FIG. 3, is the projection of that 3-dimensional cutting plane. The cutting plane is used to divide the lesion region 204 (shown in FIG. 2) into two parts; potential lesion region 207 and potential vessel region 208. This division of the original lesion region 204 is performed in a 3-dimensional sense, i.e. the region is divided as a 3-dimensional object”; Note: the anatomically relevant path, shown by the line 206 in Fig. 3, is determined as a cutting plane, which is an interface of the 3D object of the lesion and the 3D object of the vessel; see screenshot of Fig. 3 below).
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Screenshot of Fig. 3 (taken from Gindele)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Gindele to have the path be along an interface of the 3D object and another anatomical structure. In Verdonck, the path was intended for better viewing of the tortuous structure (like a blood vessel), but in cases like in Weese where there is a lesion (Page 10 lines 19-21), it would be beneficial to have the path be along the interface of the lesion and surrounding objects to have better viewing of the lesion for determining its properties and making a diagnosis.
Claims 17 are rejected under 35 U.S.C. 103 as being unpatentable over Weese in view of Samset, Shukla, and Liang.
Regarding claim 17, Weese in view of Samset and Shukla teaches the system according to claim 15. Weese does not teach wherein the processor subsystem is configured: to open an interactive display panel showing involvement of a tumor with the anatomical object and metrics regarding the involvement, or metrics regarding the involvement per slice; and to synchronize the interactive display panel, the 2D view and the 3D view. However, Liang teaches opening an interactive display panel showing involvement of a tumor with the anatomical object and metrics regarding the involvement, or metrics regarding the involvement per slice (Paragraph 0040-0041 – “An exemplary embodiment for enabling a user to define a safety margin will now be described, with reference to FIG. 2a, which shows a representation of a safety margin indicator 201 surrounding a lesion or tumor 204 of an anatomical structure 205 (e.g., a liver), depicted in 3D space (i.e., in region 102 of FIG. 1). A safety margin can be useful to define an area for resection, for example, that includes both the lesion or tumor 204 and an additional buffer area around it for additional precautionary reasons…the size and shape of the safety margin indicator 201 can be specified and adjusted by the user 821 by way of a user interface”; Note: there is an interactive display (user interface) for showing a tumor, surrounding anatomical objects, and a safety indicator, which is a type of metric regarding the involvement of the tumor and the other anatomical objects); and to synchronize the interactive display panel, the 2D view and the 3D view (Fig. 1, Paragraph 0040-0041 – “An exemplary embodiment for enabling a user to define a safety margin will now be described, with reference to FIG. 2a, which shows a representation of a safety margin indicator 201 surrounding a lesion or tumor 204 of an anatomical structure 205 (e.g., a liver), depicted in 3D space (i.e., in region 102 of FIG. 1)…the size and shape of the safety margin indicator 201 can be specified and adjusted by the user 821 by way of a user interface… The safety margin indicator 201 is displayable in both 3D and 2D in the regions 102 and 103, respectively, and the size, shape, and/or location of the indicator 201, where adjusted by the user (via, e.g., the user interface 804), are updated in the display region(s) substantially instantaneously by the system 800”; Note: edits by the user are updated in the display. This means that the interactive display panel, which is the user interface, is synchronized with the 2D view and 3D view in regions 102 and 103 respectively, in Fig. 1). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Liang to have an interactive display panel showing a tumor with an anatomical object and their metrics because “The foregoing capabilities for adjusting the safety margin indicator 201 can be beneficial when, for example, multiple lesions/tumors, requiring differently sized and/or shaped safety margin indicators, are to be re-sectioned in a single operative setting. Real time visual feedback provided by the system 800 is especially useful when the user interactively adjusts the size or the like of the safety margin indicator 201 as described above” (Liang: paragraph 0041). In other words, displaying a tumor in its own interactive panel provides different views and annotations of the tumor and may help the user in determining the diagnosis and treatability. It also would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Weese to incorporate the teachings of Liang to synchronize the interactive display and 2D and 3D views for the benefit of being able to use all of the views together, so that they can supplement each other. This would enhance the user experience and increase their understanding of the condition.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kumar et al. (US 20210027883 A1) teaches a method of assisting in clinical decision making of patient images by selecting a workflow for analyzing the images. Ribes et al. (US 20160113632 A1) teaches a method of generating a 3D ultrasound image, which involves selecting an algorithm to segment the acquired ultrasound image.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 MICHELLE HAU MA whose telephone number is (571)272-2187. The examiner can normally be reached M-Th 7-5:30.
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/MICHELLE HAU MA/ Examiner, Art Unit 2617
/KING Y POON/Supervisory Patent Examiner, Art Unit 2617
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