Encoder-Decoder Cell and Nuclei segmentation models
ImageJ macro for the analysis of foci (e.g. DNA damage) in nuclei/cells
Large-scale cell segmentation with cellpose.
Graphical tool for creating image segmentation annotations and training custom Cellpose models
Comprehensive pipeline for cell segmentation, tracking, and correlation analysis in time-lapse microscopy data. Utilizes deep learning models (Cellpose) for segmentation, with integrated refinement, tracking, and correlation analysis of dynamic cellular behaviors. Developed as part of a Master’s thesis project at KTH Royal Institute of Technology.
Wrapper code for segmentation of cells and nuclei with Cellpose.
Mammary cell shape computation over time with Trackmate-Cellpose
This repository provides StarDist and CellPose models, meticulously trained on a large dataset of Pancreatic Ductal Adenocarcinoma organoids co-cultured with immune cells. Pre-print available at https://www.biorxiv.org/content/10.1101/2024.02.12.580032v1. Demo application available at https://segmentorganoids.streamlit.app/
End-to-end pipeline for spinal-cord microscopy segmentation with Cellpose, tiling, and mask stitching.
Example workflows for image processing, segmentation and analysis. Stitching and alignment functions also implemented.
Python Instance (map) Eikonal Function Solver
Segmentation of microscopy images and data analysis pipeline with a graphical user interface, powered by Cellpose.
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
Open Call #1: Segmentation and Tracking of Epithelial Cells
A snakemake pipeline to perform cell segmentation on MERFISH spatial transcriptomics data.
Открытый репозиторий с Jupyter-блокнотами для анализа микрореологических свойств эритроцитов с помощью машинного обучения, включая сегментацию и оценку деформируемости клеток
Advanced cell seeding efficiency analysis using CellPose AI segmentation with GPU acceleration. Automated classification of seed cells, fixed cells, dead cells, and debris with real-time progress tracking and comprehensive visualization outputs.
Single cell resolution 3D imaging and segmentation within intact live tissues
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