pyorganoidnet
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/
Science Score: 67.0%
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○Scientific vocabulary similarity
Low similarity (9.2%) to scientific vocabulary
Keywords
Repository
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/
Basic Info
- Host: GitHub
- Owner: ajinkya-kulkarni
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://zenodo.org/records/10643410
- Size: 60.9 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 1
Topics
Metadata Files
README.md
OrganoIDNetData: Pancreatic Ductal Adenocarcinoma Organoid Dataset
Introduction
Welcome to the OrganoIDNetData repository. This public dataset is a significant step forward in cancer research, particularly in the study of Pancreatic Ductal Adenocarcinoma (PDAC). It comprises phase-contrast images of murine and patient-derived tumor organoids co-cultured with immune cells. With 190 images and 33,906 organoids, OrganoIDNetData serves as a potential benchmark for organoid segmentation models in oncological research. The pre-print based on this work can be found here.
Dataset Overview
- Type of Cancer: Pancreatic Ductal Adenocarcinoma
- Images: 190 phase-contrast images
- Organoids Count: 33,906
- Culturing: Co-cultured with immune cells
- Focus: Tumor organoids
Objective
The primary objective of OrganoIDNetData is to address the challenges in organoid research, particularly: - Efficient and reliable segmentation of organoid images - Quantification of organoid growth, regression, and response to treatments - Prediction of organoid system behaviors
Usage
This dataset is intended for use in developing and testing algorithms for: - Object detection and segmentation in organoid images - Machine learning models in oncology research - Benchmarking against other organoid segmentation models
Contributing
We welcome contributions to OrganoIDNetData! If you have suggestions or improvements, please fork the repository and submit a pull request.
Owner
- Name: Ajinkya Kulkarni
- Login: ajinkya-kulkarni
- Kind: user
- Location: Göttingen
- Company: Max Planck Institute for Multidisciplinary Sciences
- Website: https://orcid.org/0000-0003-1423-3676
- Twitter: kulkajinkya
- Repositories: 5
- Profile: https://github.com/ajinkya-kulkarni
Image Data Scientist @mpi_nat working in Translational Oncology
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Kulkarni" given-names: "Ajinkya" orcid: "https://orcid.org/0000-0003-1423-3676" title: "PyOrganoIDNet" version: 1.0 doi: 10.5281/zenodo.10630731 date-released: 2024-02-07 url: "https://github.com/ajinkya-kulkarni/PyOrganoIDNet"