# US 2023/0410339 A1 · Generating views of skin lesions for improved remote evaluation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0410339 A1 - Document ID: US20230410339A1 - Status: Published application - Kind: A1 - Application number: 18/203,922 - Filed: 2023-05-31 - Published: 2023-12-21 - Earliest claimed: 2022-06-13 - Assignees: Koninklijke Philips N.V. - Applicants: Koninklijke Philips N.V. - Inventors: Abhivyakti Sawarkar; Ayushi Sinha - Web page: https://patentgrep.com/patent/US20230410339A1 ## CPC - G06T 7/55: from multiple images - G06T 17/00: Three-dimensional [3D] modelling for computer graphics - A61B 5/0013: {Medical image data (A61B1/00011, A61B6/56, A61B8/56 take precedence)} - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/0895: Weakly supervised learning, e.g. semi-supervised or self-supervised learning - G16H 30/40: for processing medical images, e.g. editing - H04N 23/633: {for displaying additional information relating to control or operation of the camera} - 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} - A61B 5/0077: {Devices for viewing the surface of the body, e.g. camera, magnifying lens} - A61B 5/441: {Skin evaluation, e.g. for skin disorder diagnosis} - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/30088: Skin; Dermal - G06T 2207/30096: Tumor; Lesion - G06T 2210/41: Medical - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - 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 - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract A method for generating a continuous digital volumetric representation of a region of a patient, comprising: (i) receiving, by a volumetric representation generation system, an instruction or request to generate a digital volumetric representation of the region of the patient; (ii) providing one or more guidance instructions regarding obtaining a plurality of images of the region; (iii) receiving the plurality of images, wherein at least of each of two or more of the plurality of images are obtained of the region of the patient from a different angle; (iv) processing, using a trained model, the received plurality of images to generate a continuous digital volumetric representation of the region; and (v) providing the generated continuous digital volumetric representation of the region to a user. ## Claims ### Claim 1 A method for generating a continuous digital volumetric representation of a region of a patient, comprising: receiving by a volumetric representation generation system, an instruction or request to generate a digital volumetric representation of the region of the patient; providing, to the patient via a user interface, one or more guidance instructions regarding obtaining a plurality of images of the region of the patient; receiving a plurality of images obtained of the region of the patient, wherein at least of each of two or more of the plurality of images are obtained of the region of the patient from a different angle; processing using a trained model, the received plurality of images to generate a continuous digital volumetric representation of the region; and providing the generated continuous digital volumetric representation of the region to a user. ### Claim 2 (depends on 1) The method of claim 1, wherein the trained model is further configured to generate, by processing the received plurality of images, a confidence level for the generated continuous digital volumetric representation of the region. ### Claim 3 (depends on 1) The method of claim 1, further comprising the steps of: providing, to the patient via the user interface, an instruction to obtain one or more images of the region of the patient, wherein the instruction is based on the generated continuous digital volumetric representation of the region; receiving one or more images of the region of the patient; and re-processing, using the trained model, the received plurality of images and the received one or more images to generate an updated continuous digital volumetric representation of the region ### Claim 4 (depends on 1) The method of claim 1, wherein the plurality of images obtained of the region of the patient are obtained using a digital camera. ### Claim 5 (depends on 1) The method of claim 1, further comprising: processing one or more generated continuous digital volumetric representations of the region, the one or more generated continuous digital volumetric representations of the region generated from a plurality of images of the region of the patient obtained at one or more different times; and computing, based on the one or more generated continuous digital volumetric representations of the region, one or more clinically-relevant metrics and/or risks. ### Claim 6 (depends on 1) The method of claim 1, further comprising training the model to process a received plurality of images of a region to generate at least a continuous digital volumetric representation of the region. ### Claim 7 A method for manipulating a continuous digital volumetric representation of a region of a patient, comprising: receiving a generated continuous digital volumetric representation of a region of a patient, wherein the continuous digital volumetric representation of the region of the patient is generated by the process: receiving, by the system, an instruction or request to generate a digital volumetric representation of the region of the patient; providing to the patient via a user interface, one or more guidance instructions regarding obtaining a plurality of images of the region of the patient; receiving a plurality of images obtained of the region of the patient, wherein at least of each of two or more of the plurality of images are obtained of the region of the patient from a different angle; processing, using a trained model, the received plurality of images to generate the continuous digital volumetric representation of the region; and manipulating, using a visualization controller and user interface, the received continuous digital volumetric representation, wherein manipulation comprises at least viewing the received continuous digital volumetric representation from two or more different angles. ### Claim 8 (depends on 7) The method of claim 7, wherein the plurality of images obtained of the region of the patient are obtained using a digital camera. ### Claim 9 (depends on 8) The method of claim 8, wherein the digital camera is a component of a wearable device or a smartphone of the patient. ### Claim 10 A system for generating a continuous digital volumetric representation of a region of a patient, comprising: a plurality of images obtained of a region of a patient, wherein at least of each of two or more of the plurality of images are obtained of the region of the patient from a different angle; a trained volumetric representation model; a processor configured to analyze, using the trained volumetric representation model, the received plurality of images to generate a continuous digital volumetric representation of the region; a user interface configured to provide the generated continuous digital volumetric representation of the region to a user. ### Claim 11 (depends on 10) The system of claim 10, wherein the processor is further configured to receive an instruction or request to generate a digital volumetric representation of the region of the patient, and wherein the user interface is further configured to provide one or more guidance instructions regarding obtaining a plurality of images of the region of the patient. ### Claim 12 (depends on 10) The system of claim 10, wherein the processor is further configured to: (i) provide an instruction to obtain one or more images of the region of the patient, wherein the instruction is based on the generated continuous digital volumetric representation of the region; (ii) receive one or more images of the region of the patient; and (iii) re-process, using the trained volumetric representation model, the received plurality of images and the received one or more images to generate an updated continuous digital volumetric representation of the region. ### Claim 13 (depends on 10) The system of claim 10, wherein the plurality of images obtained of the region of the patient are obtained using a digital camera. ### Claim 14 (depends on 13) The system of claim 13, wherein the digital camera is a component of a wearable device or a smartphone of the patient. ### Claim 15 (depends on 9) The system of claim 9, wherein the processor is further configured to train the volumetric representation model to process a received plurality of images of a region to generate at least a continuous digital volumetric representation of the region.