QuPath - Bioimage analysis & digital pathology

Integrated Cell project implemented in pytorch

Shape-Out has been superseded by Shape-Out 2.

Track 2D cell motion and mitosis in time-lapse microscopy

This remote module contains classes related to segmentation of biological cells. It has classes to represent cells' shape, color, and growth state. It also has classes to represent a cell genome, whose expression is modeled by differential equations.

High Intensity Peak Analysis for detecting High Intensity Cells

A small tool in python to read the bright-field image data and the phase image data recovered from a Digital holographic microscope (DHM) and segment the nuclei to calculate physical parameters like roughness and volume.

GO Webapp for the HIPA Tool

HIPA Tool GUI

Visualize similar cells on a 2D plot using t-SNE

manipulation and analysis of phase microscopy data

Convert experiment dataset of cells into one csv format.

Deep Learning based segmentation and tracking to understand the dynamics and morphology of cells over time.