mitosis-detection

Deeply Learnt Models :p

Spatial-Temporal Mitosis Detection in Phase-Contrast Microscopy via Likelihood Map Estimation by 3DCNN, in EMBC2020

Given an image of cells from a WSI, identify the mitotic figures and return a mitotic index.

Final thesis

A project for detection of mitotic cells from tissue images using Computer Vision.

Repository for mitosis detection using deep learning techniques

Explainable AMF vs NMF classification in H&E histopathology using Virchow2 + LoRA fine-tuning, 4-fold ensemble, and dual XAI (Attention Rollout + Grad-CAM++). Achieves 0.861 balanced accuracy on MIDOG25 + AMI-BR dataset.

This repository contains a Python application using OpenCV for detecting mitosis in images. Aimed at researchers and biologists, it provides tools to automate the counting and identification of mitotic figures in microscopic images, supporting studies in cellular biology and medical diagnostics.

A modular web platform for automated fluorescence microscopy image analysis

Automated tracking and interactive visualization/simulation of select cellular processes

SGT-DFO: Anisotropic Spatiotemporal Graph Transformer with Differentiable Graph-Flow Optimization for 3D+time cell tracking, mitosis lineage reconstruction, and light-sheet microscopy segmentation (CZ Biohub Challenge).

The code base of the IXNAnalysis toolkit developed by the Joglekar Lab (main contributors: Chu Chen, Ajit Joglekar, and Rebekah Ronan)