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公开(公告)号:US20220028068A1
公开(公告)日:2022-01-27
申请号:US17380207
申请日:2021-07-20
Applicant: NEC Laboratories America, Inc.
Inventor: Eric Cosatto , Kyle Gerard
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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公开(公告)号:US12198331B2
公开(公告)日:2025-01-14
申请号:US17380207
申请日:2021-07-20
Applicant: NEC Laboratories America, Inc.
Inventor: Eric Cosatto , Kyle Gerard
IPC: G06T7/00 , G06F18/214 , G06F18/2415 , G06T7/149 , G06V10/25
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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