Nucleia image segmentation with U-net...
ImageJ scripts for: (a) batch opening confocal files with two channels and merging them and (b) for a batch of confocal images with two channels, identifying nuclei as ROIs using one channel and quantifying the mean pixel intensity of each ROI using the other channel, and outputting results in Excel. Requirements and assumptions are in comments.
NUCLEI SEGMENTATION USING STARDIST AND PYTHON IN GOOGLE COLAB
WhoIsWho is Google Colab-based tool that aims to classify cells based on features related to their nuclei and their neighbours.
Selected Topics in Visual Recognition using Deep Learning, NYCU. CodaLab competition - Instance Segmentation
Multi-scale nuclei segmentation model for breast cancer histopathology using contextual patches, VGG16-based feature extraction, channel attention, and a U-Net decoder. Official Python implementation of the ISBI 2025 paper “M3-Net” with training, evaluation, and visualization workflows.
đźź Create and manipulate geometric shapes easily with this straightforward library designed for efficient rendering and computation.
Implementation of image segmentation networks using pytorch.
Using Deep Learning techniques for nuclei segmentation. Data extracted from Kaggle competition 2018 Data Science Bowl
Nuclei Segmentation using ResUNet
NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation
Nuclei instance segmentation with dual-decoder UNet architecture.
Performs instance segmentation and classification of nuclei in Multi-Tissue Histology WSIs(generally 100k*100k pixels).
MIC-MAQ for Microscopy Images of Cells - Multi Analyses and Quantifications is an ImageJ/Fiji Plugin for automatic segmentation of nuclei and/or cells for quantifications in other channels including foci detection
VitaminP: a vision transformer-assisted multimodal integration network for pathology cell segmentation
VitaminPScope – VitaminPScope — AI Digital Pathology Viewer for Whole-Slide Images (WSI)
pytorch implement of AD-GAN
A Napari plugin for automated cell nuclei detection, cell proliferation & population growth analysis, and single-cell tracking in brightfield and fluorescence microscopy images
compact version of the official hovernet impl in pytorch
Predicting breast cancer outcomes using ML.
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