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HistoSeg is an Encoder-Decoder DCNN which utilizes the novel Quick Attention Modules and Multi Loss function to generate segmentation masks from histopathological images with greater accuracy. This repo contains the code to Test and Train the HistoSeg
computational-pathology-pipeline
DAN-NucNet: A dual attention based framework for nuclei segmentation in cancer histology images under wild clinical conditions