ArticleDevelopment (Cambridge, England)2021
MOrgAna: accessible quantitative analysis of organoids with machine learning.
Article in Development (Cambridge, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
60 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.
- Pooled it
- Lung Organoids: Systematic Review of Recent Advancements and its Future Perspectives.Tissue engineering and regenerative medicine · 2024Pooled it
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- From stem cells to somites: Revealing genetic and exogenous factors of human embryogenesis.Stem cell reports · 2026Article
- Generation of Budoids: 3D Multilineage Limb Models From Mouse Embryonic Stem Cells.Bio-protocol · 2026Article
- From pixels to patterns: the AI revolution in stem cell-derived models.Nature methods · 2026Review
- Shape factor analysis as a quantitative framework for assessing spheroid and organoid morphology and invasiveness.APL bioengineering · 2026Article
- Harnessing human tumor organoids for cancer modeling and precision therapy.Protein & cell · 2026Review
- Bioengineering advances in pancreatic cancer organoids for reproducible tumor microenvironment modeling.iScience · 2026Review
- Human organoids: Fit for drug discovery?Stem cell reports · 2026Review
- A quantitative pipeline for whole-mount deep imaging and analysis of multi-layered organoids across scales.eLife · 2026Article
- BrAIn: A comprehensive artificial intelligence-based morphology analysis system for brain organoids and neuroscience.Bioengineering & translational medicine · 2026Article
- Shape Factor Analysis as a Quantitative Framework for Assessing Spheroid and Organoid Morphology and Invasiveness.bioRxiv : the preprint server for biology · 2026Article
- Organoids in drug development: from predictive models to regulatory integration.Drug discovery today · 2026Review
- Kidney Organoids in Drug Development: Integrating Technological Advances and Standardization for Effective Implementation.Advanced healthcare materials · 2026Review
- An automated image analysis pipeline for wide-field optical redox imaging of patient-derived cancer organoids.Scientific reports · 2026Article
- Fast learning-free organoid quantification and tracking with OrganoSeg2.Scientific reports · 2026Article
- Advances in organoid imaging and automated morphometric analysis: from optical microscopy to computational approaches.Frontiers in cell and developmental biology · 2026Review
- A deep learning-based computational pipeline predicts developmental outcome in retinal organoids.PLoS biology · 2026Article
- AI and organoid platforms for brain-targeted theranostics.Theranostics · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent years have seen a dramatic increase in the application of organoids to developmental biology, biomedical and translational studies. Organoids are large structures with high phenotypic complexity and are imaged on a wide range of platforms, from simple benchtop stereoscopes to high-content confocal-based imaging systems. The large volumes of images, resulting from hundreds of organoids cultured at once, are becoming increasingly difficult to inspect and interpret. Hence, there is a pressing demand for a coding-free, intuitive and scalable solution that analyses such image data in an automated yet rapid manner. Here, we present MOrgAna, a Python-based software that implements machine learning to segment images, quantify and visualize morphological and fluorescence information of organoids across hundreds of images, each with one object, within minutes. Although the MOrgAna interface is developed for users with little to no programming experience, its modular structure makes it a customizable package for advanced users. We showcase the versatility of MOrgAna on several in vitro systems, each imaged with a different microscope, thus demonstrating the wide applicability of the software to diverse organoid types and biomedical studies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.