sc-MTOP is an analysis framework based on deep learning and computational pathology. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. This code provide 1) Hover-Net-based nuclear segmentation and classification; 2) Nuclear morphological and texture feature extraction; 3) Multi-level pairwise nuclear graph construction and spatial topological feature extraction.
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