Multi-scale tumor cell detection and classification
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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