| CPC G16H 50/20 (2018.01) [G06F 40/174 (2020.01); G06F 40/186 (2020.01); G06T 7/0012 (2013.01); G06T 11/60 (2013.01); G06V 10/235 (2022.01); G06V 10/764 (2022.01); G06V 10/945 (2022.01); G06V 10/987 (2022.01); G06V 20/70 (2022.01); G16H 15/00 (2018.01); G16H 30/40 (2018.01); G06T 2200/24 (2013.01); G06T 2207/20092 (2013.01)] | 10 Claims |
|
10. A method for continually regenerating adaptive, structured, reports in association with an image, the method comprising:
capturing and displaying, with an imager and display, images of patient anatomy in a graphical user interface;
applying, with a processor coupled with the imager and display, an artificial intelligence algorithm corresponding to a clinical diagnosis of the patient anatomy, to the images to graphically annotate each image with a vector-defined boundary tag overlaid on the image and to classify each displayed image with a classification label in correlation with the displayed image;
displaying, with the processor, a report on the graphical user interface, wherein the report includes fields populated based on clinical diagnoses by,
applying rule-based retrieval to retrieve a first descriptor from a templatised database, wherein the first descriptor correlates to the vector-defined boundary tag and fills a corresponding field of the report, and
applying rule-based retrieval to retrieve a second descriptor from a templatised database, wherein the second descriptor correlates to the classification label and fills a corresponding field of the report; and
receiving, from a user through the graphical user interface, a third input, wherein the third input is displayed as classification labels correlative to conditions, from a prepopulated list of classification labels, from a communicably coupled conditions database, in correlation with a read, and artificially intelligence parsed, image per patient, by a third master input mechanism including,
a first set of slave input mechanisms, communicably coupled to a corresponding third master input mechanism,
a hierarchical tree structure defined such that for each first input, at the second master input mechanism, a corresponding second set of slave input mechanisms are triggered for enabling a user to enter a second input, correlative to the first input of conditions, and
a second input or a second user-engagement, related to sub-conditions, and correlative sub-classification labels, that are associated with the first set of pre-defined conditions, wherein, the conditions database is dynamically configured and coupled with the descriptor database such that any change of parameter spatial, temporal, qualitative, quantitative of the vector-defined boundary tag cause a change by means of retrieval from a database in selection of a descriptor from the descriptor database.
|