MULTI-SCALE TUMOR CELL DETECTION AND CLASSIFICATION

    公开(公告)号:US20220028068A1

    公开(公告)日:2022-01-27

    申请号:US17380207

    申请日:2021-07-20

    Abstract: Methods and systems for training a machine learning model include generating pairs of training pixel patches from a dataset of training images, each pair including a first patch representing a part of a respective training image, and a second patch, centered at the same location as the first, representing a larger part of the training image, being resized to a same size of as the first patch. A detection model is trained using the first pixel patches, to detect and locate cells in the images. A classification model is trained using the first pixel patches, to classify cells according to whether the detected cells are cancerous, based on cell location information generated by the detection model. A segmentation model is trained using the second pixel patches, to locate and classify cancerous arrangements of cells in the images.

    Multi-scale tumor cell detection and classification

    公开(公告)号:US12198331B2

    公开(公告)日:2025-01-14

    申请号:US17380207

    申请日:2021-07-20

    Abstract: Methods and systems for training a machine learning model include generating pairs of training pixel patches from a dataset of training images, each pair including a first patch representing a part of a respective training image, and a second patch, centered at the same location as the first, representing a larger part of the training image, being resized to a same size of as the first patch. A detection model is trained using the first pixel patches, to detect and locate cells in the images. A classification model is trained using the first pixel patches, to classify cells according to whether the detected cells are cancerous, based on cell location information generated by the detection model. A segmentation model is trained using the second pixel patches, to locate and classify cancerous arrangements of cells in the images.

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