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OrgLine: A versatile pipeline for organoid morphometry using detector-guided prompts
Xun Deng1, Xinyu Hao2, Thomas Herget3
1The Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China; University of Chinese Academy of Sciences, Beijing, China.
Cell Reports Methods
|June 8, 2026
Summary
OrgLine is a new quantitative analysis pipeline for patient-derived organoids. This tool automates the analysis of organoid morphology from bright-field images, improving disease modeling and drug development.
Area of Science:
- Biotechnology
- Bioinformatics
- Cell Biology
Background:
- Patient-derived organoids are vital tools in disease modeling, drug development, and precision medicine.
- Manual analysis of organoids in 3D culture is challenging and prone to artifacts in bright-field images.
- Quantitative assessment of organoid morphology is crucial but complicated by imaging limitations.
Purpose of the Study:
- To develop an automated quantitative analysis pipeline for patient-derived organoids.
- To address the limitations of manual workflows and image artifacts in organoid analysis.
- To enable accurate morphological characterization and segmentation of organoids.
Main Methods:
- Development of OrgLine, a quantitative analysis pipeline for organoids.
- Utilizing a large, curated dataset of bright-field organoid images.
- Implementation of a detector coupled with a prompt-guided segmentation module.
Main Results:
- OrgLine accurately recognizes organoids in bright-field images.
- The pipeline enables quantitative characterization of morphological phenotypes across developmental stages.
- Accurate instance segmentation for downstream morphometric assessment is achieved.
Conclusions:
- OrgLine facilitates more automated and quantitative organoid cultivation workflows.
- The pipeline enhances the utility of patient-derived organoids in research and clinical applications.
- OrgLine improves the reliability and efficiency of organoid analysis.
