Encoder-Decoder Cell and Nuclei segmentation models

Cell (Nuclei) Detection in ROI using Stardist

The code implementation for cell segmentation

Intel OpenVINO extension for QuPath, a digital pathology platform

Instance & Semantic сегментация клеток и ядер на цитологических изображениях (мазок Папаниколау)

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/

Package using StarDist and Python that performs object detection and spatial analysis on H&E images

Quantification of Myogenic Differentiation using Deep Learning

Pipeline meant to segment and classify organoids, or any other blob-like structures (star-convex polygons). Microscopy images can be easily annotated in QuPath and automatically processed afterwards to count the class distribution within each image using this pipeline (TIF files will be converted to grayscale)

Cell segmentations using Stardist and Watershed method.

nuclei segmentation by treshold, watershed methods & stardist neural network (educational project)

Myovision Consulting Report

script to create labels (for training a deep neural network) based on nucleus segmentation using StarDist (still experimental)

NUCLEI SEGMENTATION USING STARDIST AND PYTHON IN GOOGLE COLAB