METHOD FOR TRAINING AND USING A DEEP LEARNING ALGORITHM TO COMPARE MEDICAL IMAGES BASED ON DIMENSIONALITY-REDUCED REPRESENTATIONS

    公开(公告)号:US20250086933A1

    公开(公告)日:2025-03-13

    申请号:US18566265

    申请日:2021-06-29

    Applicant: Brainlab AG

    Abstract: Disclosed is i.a. a computer-implemented method of determining a similarity between medical images which encompasses determining patches, i.e. subsets, of a medical image which is newly input to a data storage and of medical images which has been previously stored, analysing the patches for similar image features in a dimensionality-reduced reference system used for defining the image features, computing a distance between the image features in the dimensionality-reduced reference system, and based on the result of comparing the distances calculated for the newly input image and the previously stored medical images, determining whether the medical images are similar and for example originate from the same patient. Artificial intelligence is used to generate the dimensionality-reduced representation of the image features, i.e. to encode the medical images for further processing by the methods and the system disclosed herein.

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