Scalable Instance Segmentation using PyTorch & PyTorch Lightning.

Count-Ception: Counting by Fully Convolutional Redundant Counting

Cell localization and counting: 1) Exponential Distance Transform Maps for Cell Localization; 2) Multi-scale Hypergraph-based Feature Alignment Network for Cell Localization; 3) Lite-UNet: A lightweight and efficient network for cell localization

This program is implemented to count the number of cells in the image. The cells are also labeled and the perimeter and area are calculated for each cell.

The code of paper: Lite-UNet: A Lightweight and Efficient Network for Cell Localization

Efficient point process inference for large scale object detection

Analysis and characterisation of cells within the gut wall using deep learning models. The current focus is on studying enteric neurons and enteric glia.

Counting number of cell in a picture of cells

Medical Image processing and segmentation for the automatic detection and counting of blood platelets and WBCs.

braincellcount: count cells in mouse brains

SuperDSM is a globally optimal segmentation method based on superadditivity and deformable shape models for cell nuclei in fluorescence microscopy images and beyond.

Semi-automated script for detection and quantification of c-Fos cells in IHC stained confocal stack images

Cell image analysis pipeline for RPE cell identification, counting and maturity classification

Website for counting cells on a image

Non invasive live cell cycle monitoring using a supervised deep neural autoencoder onquantitative phase images

A demonstration script for analyzing cell density in whole slide images (WSIs). This repository accompanies the article published on daangeijs.nl. The demo showcases how to compute cell density in detected tumor regions using WholeSlideData and GeoPandas.

Region-based Fitting of Overlapping Ellipses (original implementation by C. Panagiotakis and A.A. Argyros, Image Vis Comput 2020)

인공지능 기술을 활용한 세포 계수 서비스

A short workshop for Matlab

Plugins for ImageJ/FIJI