# US 2025/0156502 A1 · Information processing system, information processing apparatus, information processing method, and non-transitory storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0156502 A1 - Document ID: US20250156502A1 - Status: Published application - Kind: A1 - Application number: 19/020,911 - Filed: 2025-01-14 - Published: 2025-05-15 - Earliest claimed: 2020-10-06 - Assignees: Canon Kabushiki Kaisha - Applicants: Canon Kabushiki Kaisha - Inventors: Kohtaro Umezawa; Ryuta Ueda - Web page: https://patentgrep.com/patent/US20250156502A1 ## CPC - G06F 18/2431: Multiple classes - A61B 5/0013: {Medical image data (A61B1/00011, A61B6/56, A61B8/56 take precedence)} - A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging - A61B 5/7267: {involving training the classification device} - G06F 18/285: {Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system} - G06F 18/40: Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor - G06V 10/87: {using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system} - G16H 30/20: for handling medical images, e.g. DICOM, HL7 or PACS - G16H 30/40: for processing medical images, e.g. editing - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients - A61B 2576/00: Medical imaging apparatus involving image processing or analysis (A61B1/00009, A61B6/52 and A61B8/52 take precedence) - G06V 2201/03: Recognition of patterns in medical or anatomical images - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract An information processing apparatus according to an exemplary embodiment of the present disclosure includes a storage unit configured to store a plurality of trained models including a first trained model for classifying medical image data into a class belonging to a first class hierarchy, and a second trained model for classifying the medical image data into a class belonging to a second class hierarchy lower than the first class hierarchy, an acquisition unit configured to acquire information about inference, a selection unit configured to select a plurality of trained models having a hierarchical relationship from among the stored plurality of trained models, based on the acquired information about inference, and a notification unit configured to provide a notification of the selected plurality of trained models. ## Claims ### Claim 1 An information processing apparatus comprising: a storage unit configured to store a plurality of trained models including a first trained model for classifying medical image data into a class belonging to a first class hierarchy, and a second trained model for classifying the medical image data into a class belonging to a second class hierarchy lower than the first class hierarchy; an acquisition unit configured to acquire information about inference; and a selection unit configured to select a plurality of trained models having a hierarchical relationship from among the stored plurality of trained models, based on the acquired information about inference. ### Claim 2 (depends on 1) The information processing apparatus according to claim 1, wherein the information about inference is information indicating at least one of an inference target, an inference purpose, or a class. ### Claim 3 (depends on 1) The information processing apparatus according to claim 1, further comprising an inference unit configured to perform inference using the selected plurality of trained models having the hierarchical relationship. ### Claim 4 (depends on 3) The information processing apparatus according to claim 3, wherein the inference unit performs the inference starting from a trained model for classifying the medical image data into a class belonging to a highest class hierarchy among the selected plurality of trained models having the hierarchical relationship. ### Claim 5 (depends on 1) The information processing apparatus according to claim 1, wherein the selection unit calculates a degree of conformity with a trained model corresponding to each class hierarchy, based on the information about inference, and selects the plurality of trained models based on the calculated degree of conformity. ### Claim 6 (depends on 5) The information processing apparatus according to claim 5, wherein the selection unit selects the plurality of trained models from among trained models with the calculated degree of conformity being greater than a predetermined value. ### Claim 7 (depends on 6) The information processing apparatus according to claim 6, wherein the selection unit selects a trained model corresponding to a lowest class hierarchy and a trained model that corresponds to a class hierarchy higher than the lowest class hierarchy and has the hierarchical relationship with the trained model corresponding to the lowest class hierarchy, from among the trained models with the calculated degree of conformity being greater than the predetermined value. ### Claim 8 (depends on 6) The information processing apparatus according to claim 6, wherein the selection unit selects a trained model corresponding to a highest class hierarchy and a trained model that corresponds to a class hierarchy lower than the highest class hierarchy and has the hierarchical relationship with the trained model corresponding to the highest class hierarchy, from among the trained models with the calculated degree of conformity being greater than the predetermined value. ### Claim 9 (depends on 6) The information processing apparatus according to claim 6, wherein the selection unit selects a trained model corresponding to a highest class hierarchy and a trained model corresponding to a lowest class hierarchy from among the trained models with the calculated degree of conformity being greater than the predetermined value, and in a case where there is another class hierarchy between the highest class hierarchy and the lowest class hierarchy, the selection unit further selects a trained model corresponding to the other class hierarchy. ### Claim 10 (depends on 1) The information processing apparatus according to claim 1, wherein the acquisition unit further acquires selection information about the trained models, and the selection unit selects the plurality of trained models having the hierarchical relationship, based on the selection information. ### Claim 11 (depends on 5) The information processing apparatus according to claim 5, wherein the selection unit calculates the degree of conformity by using a trained model for classifying the class belonging to the first class hierarchy and the class belonging to the second class hierarchy. ### Claim 12 An information processing method comprising: acquiring information about inference; and selecting a plurality of trained models having a hierarchical relationship based on the acquired information about inference. ### Claim 13 (depends on 12) A non-transitory computer-readable storage medium storing a program for causing a computer to execute the information processing method according to claim 12. ### Claim 14 An information processing system comprising: a storage unit configured to store a plurality of trained models including a first trained model for classifying medical image data into a class belonging to a first class hierarchy, and a second trained model for classifying the medical image data into a class belonging to a second class hierarchy lower than the first class hierarchy; an acquisition unit configured to acquire information about inference; and a selection unit configured to select a plurality of trained models having a hierarchical relationship from among the stored plurality of trained models, based on the acquired information about inference. ### Claim 15 (depends on 14) The information processing system according to claim 14, wherein the acquisition unit acquires selection information about the trained model selected on the operation unit, and the selection unit selects the plurality of trained models having the hierarchical relationship, based on the selection information. ### Claim 16 (depends on 3) The information processing apparatus according to claim 3, wherein the inference unit performs first inference using the first trained model corresponding to the first class hierarchy among the stored plurality of trained models having the hierarchical relationship and performs second inference using a trained model corresponding to a class hierarchy lower than the first class hierarchy among the stored plurality of trained models having the hierarchical relationship. ### Claim 17 (depends on 16) The information processing apparatus according to claim 16, wherein based on a result of the first inference, the inference unit performs the second inference. ### Claim 18 (depends on 17) The information processing apparatus according to claim 17, wherein the inference unit performs the second inference by using an input that is based on the result of the first inference. ### Claim 19 (depends on 1) The information processing apparatus according to claim 1, wherein the inference target image data is medical image data.