INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM

    公开(公告)号:US20240379203A1

    公开(公告)日:2024-11-14

    申请号:US18657644

    申请日:2024-05-07

    Abstract: A processor is configured to: acquire a plurality of medical documents having different creation times; specify mutually corresponding descriptions in each of one medical document among the plurality of medical documents and at least one other medical document other than the one medical document; display the one medical document on a display; receive designation of a character string for the one medical document; and display a description of the at least one other medical document corresponding to a description including the designated character string in a manner different from other descriptions other than the description corresponding to the description including the designated character string.

    INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM

    公开(公告)号:US20220392619A1

    公开(公告)日:2022-12-08

    申请号:US17887497

    申请日:2022-08-14

    Abstract: An information processing apparatus includes at least one processor, and the processor derives a property for at least one predetermined property item which is related to a structure of interest included in an image. The processor specifies a basis region serving as a basis for deriving the property related to the structure of interest for each property item and derives a basis image including the basis region.

    IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM

    公开(公告)号:US20200342606A1

    公开(公告)日:2020-10-29

    申请号:US16927977

    申请日:2020-07-13

    Abstract: Provided are an image processing apparatus, an image processing method, and a program that can collect high-quality correct answer data used for machine learning with a simple method. The image processing apparatus includes: a first extractor that extracts a measurement target region from a medical image, using a result of learning performed using correct answer data of the measurement target region; a measurement object determination unit that determines a measurement object used to measure the measurement target region; a measurement object correction unit that corrects the measurement object in response to a command from a user; and a measurement target region correction unit that corrects the measurement target region extracted by the first extractor, using a correction result of the measurement object. The first extractor performs learning using the measurement target region corrected by the measurement target region correction unit as correct answer data.

    IMAGE ANALYSIS APPARATUS, IMAGE ANALYSIS METHOD, AND PROGRAM

    公开(公告)号:US20240127570A1

    公开(公告)日:2024-04-18

    申请号:US18481198

    申请日:2023-10-04

    Abstract: An image analysis apparatus, an image analysis method, and a program for specifying a region of interest from an image in which an arrow is assigned to the region of interest are provided.
    The above problem is solved by an image analysis apparatus including at least one processor, and at least one memory in which an instruction to be executed by the at least one processor is stored, in which the at least one processor is configured to receive an image in which an arrow is assigned to a region of interest, specify the arrow, dispose one or more region-of-interest candidates that are candidates of the region of interest in accordance with a direction of the arrow and with a distance from the arrow, calculate an interest degree for each region-of-interest candidate, and specify the region of interest from among the region-of-interest candidates based on the interest degree.

    LEARNING DEVICE, LEARNING METHOD, LEARNING PROGRAM, INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM

    公开(公告)号:US20230054096A1

    公开(公告)日:2023-02-23

    申请号:US17884525

    申请日:2022-08-09

    Abstract: A processor derives a first feature amount for an object included in an image by a first neural network, structures a sentence including description of the object included in the image to derive structured information for the sentence, and derives a second feature amount for the sentence from the structured information by a second neural network. The processor trains the first neural network and the second neural network such that, in a feature space to which the first feature amount and the second feature amount belong, a distance between the derived first feature amount and second feature amount is reduced in a case in which the object included in the image and the object described in the sentence correspond to each other.

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