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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.