# US 11,896,196 B2 · Method for enhanced data analysis with specialized video enabled software tools for medical environments > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,896,196 B2 - Document ID: US11896196B2 - Status: Granted - Kind: B2 - Application number: 18/097,202 - Filed: 2023-01-14 - Published: 2023-09-14 - Granted: 2024-02-13 - Earliest claimed: 2009-05-29 - Applicants: Jack Wade - Inventors: Jack Wade - Web page: https://patentgrep.com/patent/US11896196B2 ## CPC - A61B 1/00006: {of control signals} - A61B 1/000095: {for image enhancement} - A61B 1/00009: {of image signals during a use of endoscope} - A61B 1/00011: {characterised by signal transmission} - A61B 1/3132: {for laparoscopy} - A61B 34/25: {User interfaces for surgical systems} - A61B 90/361: {Image-producing devices, e.g. surgical cameras} - G06F 3/0481: based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance - G16H 10/00: ICT specially adapted for the handling or processing of patient-related medical or healthcare data (for medical reports G16H15/00; for therapies or health-improving plans G16H20/00; for the handling or processing of medical images G16H30/00) - G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture - G16H 30/20: for handling medical images, e.g. DICOM, HL7 or PACS - G16H 30/40: for processing medical images, e.g. editing - G16H 40/63: for local operation - G16H 40/67: for remote operation - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - H04N 7/147: {Communication arrangements, e.g. identifying the communication as a video-communication, intermediate storage of the signals (selecting H04Q)} - H04N 7/185: {from a mobile camera, e.g. for remote control} - A61B 90/30: Devices for illuminating a surgical field, the devices having an interrelation with other surgical devices or with a surgical procedure - A61B 2090/365: {augmented reality, i.e. correlating a live optical image with another image} - G06T 2200/24: involving graphical user interfaces [GUIs] - G06T 2207/30004: Biomedical image processing - G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients - H04L 67/125: involving control of end-device applications over a network - H04N 7/183: {for receiving images from a single remote source} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract Medical software tools platforms utilize a surgical display to provide access to specific medical software tools, such as medically-oriented applications or widgets, that can assist surgeons or surgical team in performing various procedures. In particular, an endoscopic camera may register the momentary rise in the optical signature reflected from a tissue surface and in turn transmit it to a medical image processing system which can also receive patient heart rate data and display relevant anomalies. Changes in various spectral components and the speed at which they change in relation to a source of stimulus (heartbeat, breathing, light source modulation, etc.) may indicate the arrival of blood, contrast agents or oxygen absorption. Combinations of these may indicate various states of differing disease or margins of tumors, and so forth. Also, changes in temperatures, physical dimensions, pressures, photoacoustic pressures and the rate of change may indicate tissue anomalies in comparison to historic values. ## Claims ### Claim 1 A method for processing and annotating images of patient tissue using medical software tools, comprising: generating an image stream by way of an interface module configured to receive said image stream from a camera wherein said image stream interface module includes a CPU for processing said image stream; providing a user interface overlay module configured to provide said user interface overlay adapted for presentation over said image stream by use of a video router providing a video stream to overlay an original video image; processing optical sensor data corresponding with said camera for registering changes in spectral characteristics reflected from a tissue surface under inspection wherein an optical sensor provides a signal indicative of light energy detected; utilizing a medical software tools module configured to provide said medical software tools through said user interface, said medical software tools being configured to perform an operation with said image stream and provide an output to be presented over said image stream, responsive to said light detected by said optical sensor; and utilizing a medical image processing system for processing patient data and correlating said patient medical data with momentary changes in spectral characteristics for generating said optical signature data of various patient conditions, wherein said medical software tool measures: a. changes in color intensity, b. rates at which said color intensities change in response to: heartbeat pushed blood, breathing pushed oxygen and intensity and modulation from a light source. ### Claim 2 (depends on 1) The method according to claim 1, wherein said annotations are forwarded to an external memory storage cloud and include area markers to highlight anomalous areas and areas of interest. ### Claim 3 (depends on 2) A method according to claim 2, wherein said area markers are annotated with notes pertinent to the observed tissue surfaces and are forwarded to an external memory storage cloud. ### Claim 4 (depends on 3) The method according to claim 3, wherein said area markers indicate areas wherein said image stream is digitally processed and zoomed for presentation of a zoomed in image for presentation to a user. ### Claim 5 (depends on 1) A method according to claim 1 wherein micro-blushes are detected as they appear upon said tissue surfaces captured within as blood flow rates modulate within said tissue surfaces, and wherein said detection results are forwarded to an external memory storage cloud. ### Claim 6 (depends on 1) A method according to claim 1 wherein an optical signature module facilitates processing of said patient optical signature data including heart rate data and image data and transports said data to an external memory storage cloud. ### Claim 7 (depends on 2) A method according to claim 2, wherein said medical image processing system features a toolset with a plurality of widgets configured to receive image data from said external memory storage cloud. ### Claim 8 (depends on 2) A method according to claim 2, further comprising of the medical image processing system retrieving data from a patient heart monitoring apparatus, transmitting said data to an external memory storage cloud and registering said data as patient medical data. ### Claim 9 (depends on 8) A method according to claim 8 wherein said optical signature module generates optical signature data that is transported to an external memory storage cloud. ### Claim 10 (depends on 2) A method according to claim 2 wherein optical signature data includes timer data that is transported to an external memory storage cloud. ### Claim 11 (depends on 1) A method according to claim 1 wherein said patient and medical data may be utilized by artificial intelligence engine for surgical planning and simulations to guide a medical professional performing a procedure. ### Claim 12 (depends on 11) A method according to claim 11 wherein a height intensity map is produced and used by an artificial intelligence algorithm to analyze tissue. ### Claim 13 (depends on 11) A method according to claim 11 wherein a color map is generated to be produced and used by an artificial intelligence algorithm to analyze areas of interest in response to various said spectral components generated. ### Claim 14 (depends on 11) A method according to claim 11 wherein a checklist produced by an artificial intelligence algorithm is combined with said patient optical signature data so that a user is reminded not to miss medical procedure steps. ### Claim 15 (depends on 11) A method according to claim 11 wherein said patient optical signature data is combined with margin guide data so that an artificial intelligence algorithm may define and utilize a margin of clear tissue surrounding a tissue location of interest to said medical professional. ### Claim 16 (depends on 11) A method according to claim 11 wherein said patient medical data includes images from a medical procedure that are securely stored on an external memory storage cloud for dataset creation and are used to train an artificial intelligence algorithm. ### Claim 17 (depends on 11) A method according to claim 11, wherein said annotations are forwarded to an external memory storage cloud and include area markers suggested by an artificial intelligence analysis to highlight anomalous areas and areas that may be of interest. ### Claim 18 (depends on 17) A method according to claim 17 wherein said generated area markers are compared with cloud images to compare corresponding external memory-stored tissue images between different patients undergoing a surgical procedure. ### Claim 19 (depends on 17) A method according to claim 17, wherein said medical guide includes comparisons that include a multitude of patient tissue images deriving from an external memory storage cloud to form a model of what is categorized as healthy tissue. ### Claim 20 (depends on 17) The method according to claim 17, wherein said artificial intelligence algorithm utilizes a database of historical samples deriving from an external memory storage cloud to determine anomalies and changes in tissue by comparing patient tissue sample data stored on said external memory storage cloud.