Efficient point process inference for large scale object detection
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Updated
Apr 3, 2018 - MATLAB
Efficient point process inference for large scale object detection
Medical Image processing and segmentation for the automatic detection and counting of blood platelets and WBCs.
Non invasive live cell cycle monitoring using a supervised deep neural autoencoder onquantitative phase images
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
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.
This repository is dedicated to the AIBI 2019/2020 project. This project's objective is to automate cell counting in microscopy images.
count lipid droplets in tetrahymena with Python
Plugins for ImageJ/FIJI
The code of paper: Lite-UNet: A Lightweight and Efficient Network for Cell Localization
An immunohistochemistry cell-counting (quantifying) neural network (CSRNet PyTorch) that was trained on KRT14, KRT5, and Ki67 stains (and of course DAPI).
SuperDSM is a globally optimal segmentation method based on superadditivity and deformable shape models for cell nuclei in fluorescence microscopy images and beyond.
braincellcount: count cells in mouse brains
A short workshop for Matlab
Cell image analysis pipeline for RPE cell identification, counting and maturity classification
Region-based Fitting of Overlapping Ellipses (original implementation by C. Panagiotakis and A.A. Argyros, Image Vis Comput 2020)
A simple ImageJ Macro to count the cells of multiple images.
Semi-automated script for detection and quantification of c-Fos cells in IHC stained confocal stack images
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.
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