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This repository contains my implementations of the algorithms which we used for evaluation of the MoNuSeg challenge at MICCAI 2018.
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
UNet++, UNet, SegNet and DeepLabv3 implemented in Keras for MoNuSeg dataset