# US 2021/0243358 A1 · Cognitive optical control system and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0243358 A1 - Document ID: US20210243358A1 - Status: Published application - Kind: A1 - Application number: 17/301,994 - Filed: 2021-04-21 - Published: 2021-08-05 - Earliest claimed: 2017-09-27 - Assignees: Synaptive Medical Inc. - Applicants: Synaptive Medical Inc. - Inventors: Michael Frank Gunter WOOD; Piotr KUCHNIO; Cameron Anthony PIRON - Web page: https://patentgrep.com/patent/US20210243358A1 ## CPC - H04N 23/62: Control of parameters via user interfaces - A61B 34/00: Computer-aided surgery; Manipulators or robots specially adapted for use in surgery - A61B 34/25: {User interfaces for surgical systems} - G01R 33/4812: {MR combined with X-ray or computed tomography [CT]} - G01T 1/2985: {In depth localisation, e.g. using positron emitters; Tomographic imaging (longitudinal and transverse section imaging; apparatus for radiation diagnosis sequentially in different planes, steroscopic radiation diagnosis); (using external radiation sources A61B6/02)} - G06N 5/04: Inference or reasoning models - G06N 20/00: Machine learning - G16H 30/40: for processing medical images, e.g. editing - H04N 23/64: {Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image} - H04N 23/72: Combination of two or more compensation controls - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/481: {involving the use of contrast agents} - A61B 6/5247: {combining images from an ionising-radiation diagnostic technique and a non-ionising radiation diagnostic technique, e.g. X-ray and ultrasound} - A61B 2505/05: Surgical care - A61B 2576/026: for the brain - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - G01T: MEASUREMENT OF NUCLEAR OR X-RADIATION (radiation analysis of materials, mass spectrometry G01N23/00; tubes for determining the presence, intensity, density or energy of radiation or particles H01J47/00) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract A cognitive optical system for dynamically refining imaging during a medical procedure, involving a processor operable by a set of executable instructions storable in relation to a non-transitory memory device. The processor is configured to automatically adjust an image by automatically compensating for at least one external factor affecting an anatomical area being viewed, automatically adjusting at least one imaging parameter, and automatically adjusting at least one internal control of an optical chain, whereby a quality of the image is improvable in real time. ## Claims ### Claim 1 A cognitive optical system for dynamically refining an image, having at least one imaging parameter, during a medical procedure, the system comprising: a processor operable by a set of executable instructions storable in relation to a non-transitory memory device and configured to automatically adjust the image by fine-tuning an optical chain based on at least one input parameter, the processor configured to fine-tune the optical chain by using at least one of a machine learning technique and an artificial intelligence technique, the processor configured to perform any dynamic parameter adjustment by using a hierarchal structure, whereby optimization degradation of one imaging parameter of the at least one imaging parameter by optimization of another imaging parameter of the at least one imaging parameter is avoided, and the processor configured to fine-tune the optical chain by effecting micro-adjustments thereto. ### Claim 2 (depends on 1) The system of claim 1, wherein the processor is further configured to automatically adjust the image by: automatically compensating for at least one external factor affecting an anatomical area being viewed; automatically adjusting the at least one imaging parameter; automatically adjusting at least one internal control of the optical chain, automatically adjust the image based on the at least one input parameter, the at least one input parameter comprising at least one of a host tissue type, a pathology type, an optical chain variable, and a plurality of user experience data via a preoperative input device, and at least one of receive input from, and transmit output to, an intraoperative input device, the intraoperative input device receiving the input from a plurality of components, the plurality of components comprising at least one navigation device and at least one external device, and the plurality of components further comprising one of at least one advanced optical device and at least one spectroscopic device, and wherein the optical chain comprises at least one of optical software, optical firmware, and optical hardware. ### Claim 3 (depends on 1) The system of claim 1, wherein the at least one imaging parameter comprises at least one of an illumination, a saturation, a color, a contrast, and an opacity, and wherein the processor is further configured to at least one of: automatically adjust the illumination by adjusting at least one of an illumination spectrum and a luminance in relation to a camera scope, automatically adjust the color by adjusting at least one color filter in relation to a camera scope, automatically adjust the saturation by processing the image to reduce light, and automatically adjust the opacity by at least one of adjusting an infrared illumination level and applying a filter. ### Claim 4 (depends on 1) The system of claim 1, wherein the processor is further configured to automatically adjust the image based on the at least one input parameter further comprising an environmental condition. ### Claim 5 (depends on 1) The system of claim 1, wherein the set of executable instructions comprises a predictive macro-optimization instruction based on a multi-modal real-time tissue interrogation for facilitating dynamically refining imaging. ### Claim 6 (depends on 5) The system of claim 5, wherein the predictive macro-optimization instruction comprises informatics, whereby the processor is configured to determine at least one ideal condition corresponding to the at least one external factor. ### Claim 7 (depends on 1) The system of claim 1, wherein the processor is configured to instruct an imaging system to provide a prompt requesting approval of an automated adjustment of the at least one imaging parameter prior to rendering an adjusted image on a display device. ### Claim 8 (depends on 6) The system of claim 6, wherein the informatics comprises a feature for learning information relating to previous procedures. ### Claim 9 (depends on 8) The system of claim 8, wherein the information relating to the previous procedures comprises at least one type of imaging parameter for optimizing tissue differentiation. ### Claim 10 (depends on 1) The system of claim 1, wherein the at least one internal control of the optical chain comprises at least one of a zoom level, a numerical aperture, a camera type, an exposure time, an exposure gain, a de-noising strength, a local area contrast enhancement strength, a display type, a brightness level, and a contrast level. ### Claim 11 A method of fabricating a cognitive optical system for dynamically refining an image, corresponding to at least one imaging parameter, during a medical procedure, the method comprising: providing a processor operable by a set of executable instructions storable in relation to a non-transitory memory device and configured to automatically adjust the image by fine-tuning an optical chain based on at least one input parameter, providing the processor comprising configuring the processor to fine-tune the optical chain by using at least one of a machine learning technique and an artificial intelligence technique, providing the processor comprising configuring the processor to perform any dynamic parameter adjustment by using a hierarchal structure, whereby optimization degradation of one imaging parameter of the at least one imaging parameter by optimization of another imaging parameter of the at least one imaging parameter is avoided, and providing the processor comprising configuring the processor to fine-tune the optical chain by effecting micro-adjustments thereto. ### Claim 12 (depends on 11) The method of claim 11, wherein providing the processor further comprises configuring the processor to automatically adjust the image by: automatically compensating for at least one external factor affecting an anatomical area being viewed; automatically adjusting the at least one imaging parameter; automatically adjusting at least one internal control of the optical chain, automatically adjust the image based on the at least one input parameter, the at least one input parameter comprising at least one of a host tissue type, a pathology type, an optical chain variable, and a plurality of user experience data via a preoperative input device, and at least one of receive input from, and transmit output to, an intraoperative input device, the intraoperative input device receiving the input from a plurality of components, the plurality of components comprising at least one navigation device and at least one external device, and the plurality of components further comprising one of at least one advanced optical device and at least one spectroscopic device; and adjust the image by fine-tuning the optical chain, comprising at least one of optical software, optical firmware, and optical hardware, based on at least one input parameter. ### Claim 13 (depends on 11) The method of claim 11, wherein providing the processor comprises configuring the processor to automatically adjust the at least one imaging parameter comprising at least one of an illumination, a saturation, a color, a contrast, and an opacity, and wherein providing the processor comprises configuring the processor to at least one of: automatically adjust the illumination by adjusting at least one of an illumination spectrum and a luminance in relation to a camera scope; automatically adjust the color by adjusting at least one color filter in relation to a camera scope; automatically adjust the saturation by processing the image to reduce light; and automatically adjust the opacity by at least one of adjusting an infrared illumination level and applying a filter. ### Claim 14 (depends on 11) The method of claim 11, wherein providing the processor further comprises configuring the processor to automatically adjust the image based on the at least one input parameter further comprising an environmental condition. ### Claim 15 (depends on 11) The method of claim 11, wherein providing the processor comprises configuring the processor as operable by the set of executable instructions comprising a predictive macro-optimization instruction based on a multi-modal real-time tissue interrogation for facilitating dynamically refining imaging. ### Claim 16 (depends on 15) The method of claim 15, wherein providing the processor comprises configuring the processor as operable by the set of executable instructions comprising the predictive macro-optimization instruction, the predictive macro-optimization instruction comprising an instruction for using informatics, whereby the processor is configured to determine at least one ideal condition corresponding to the at least one external factor. ### Claim 17 (depends on 11) The method of claim 11, wherein providing the processor comprises configuring the processor to instruct an imaging system to provide a prompt requesting approval of an automated adjustment of the at least one imaging parameter prior to rendering an adjusted image on a display device. ### Claim 18 (depends on 16) The method of claim 16, wherein configuring the processor as operable by the set of executable instructions comprises providing a predictive macro-optimization instruction, the predictive macro-optimization instruction comprising an instruction for using informatics, the instruction for using informatics comprising providing a feature for learning information relating to previous procedures, and wherein the information relating to previous procedures comprises at least one type of imaging parameter for optimizing tissue differentiation. ### Claim 19 (depends on 11) The method of claim 11, wherein the at least one internal control of the optical chain comprises at least one of a zoom level, a numerical aperture, a camera type, an exposure time, an exposure gain, a de-noising strength, a local area contrast enhancement strength, a display type, a brightness level, and a contrast level. ### Claim 20 A method of dynamically refining an image, corresponding to at least one imaging parameter, during a medical procedure by way of a cognitive optical system, comprising: providing the cognitive optical system, providing the cognitive optical system comprising providing a processor operable by a set of executable instructions storable in relation to a non-transitory memory device and configured to automatically adjust the image by fine-tuning an optical chain based on at least one input parameter, providing the processor comprising configuring the processor to fine-tune the optical chain by using at least one of a machine learning technique and an artificial intelligence technique, providing the processor comprising configuring the processor to perform any dynamic parameter adjustment by using a hierarchal structure, whereby optimization degradation of one imaging parameter of the at least one imaging parameter by optimization of another imaging parameter of the at least one imaging parameter is avoided, and providing the processor comprising configuring the processor to fine-tune the optical chain by effecting micro-adjustments thereto; and operating the processor.