A python package which aligns histology to the Allen Brain Atlas and Waxholm rat atlas using deep learning.
A pipeline to segment tissue from the background in histological images
SIMPLI is a highly configurable pipeline for the analysis of multiplexed imaging data.
The repository contains a simple pipeline for training Nuclei Segmentation Datasets of Histopathology Images.
MICCAI 2022: Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images
adaptive color deconvolution for paper "Zheng et al., CMPB, 2019"
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
Preprocessing module for large histological images
A Point Transformer with Federated Learning for HER2 Status Prediction
Code to reproduce results of the Gigapixel Histopathological Image Analysis Using Attention-Based Neural Networks paper.
Segmentation of histological images and fibrosis identification with a convolutional neural network
This repository contains some comprehensive approaches for the purpose of classifying breast cancer tissue using whole slide images (WSIs).
[ICASSP 2025 Oral] DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images
The nuclei detection method on histology image proposed in the 2017 paper by Peikari et al.
[𝗜𝗖𝗔𝗦𝗦𝗣 𝟮𝟬𝟮𝟱 𝗢𝗿𝗮𝗹] DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images
Python library designed for tissue microenvironment spatial analysis
Deep learning for virtual staining of label-free tissue: A survey. ℱℯℯ𝓁 𝒻𝓇ℯℯ to contribute!
Course assignment ~ Classification of breast cancer histology images using Convolutional Neural Networks
Deep Learning breast histology microscopy image recognition using Convolutional Neural Networks
Research Project at ISI ( Indian Statistical Institute ), Kolkata
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