ArticleDisease models & mechanisms2023
Tellu - an object-detector algorithm for automatic classification of intestinal organoids.
Article in Disease models & mechanisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- OrgLine: A versatile pipeline for organoid morphometry using detector-guided prompts.Cell reports methods · 2026Article
- Classification of different light colors applied during the incubation period based on small intestine morphology with XGBoost algorithm.BMC veterinary research · 2026Article
- Integrating Human Intestinal Organoids into FDA's New Approach Methodologies for Drug Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Fast learning-free organoid quantification and tracking with OrganoSeg2.Scientific reports · 2026Article
- IDP-Head: An Interactive Dual-Perception Architecture for Organoid Detection in Mouse Microscopic Images.Biomimetics (Basel, Switzerland) · 2025Article
- Deliod a lightweight detection model for intestinal organoids based on deep learning.Scientific reports · 2025Article
- OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data.Cellular oncology (Dordrecht, Netherlands) · 2025Article
- More than just life and death: advances in imaging and analysis for 3D-bioprinted tissues.Frontiers in bioengineering and biotechnology · 2025Article
- Article
- [A review on depth perception techniques in organoid images].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Review
- A Curated Cell Life Imaging Dataset of Immune-enriched Pancreatic Cancer Organoids with Pre-trained AI Models.Scientific data · 2024Article
- Advanced 3D imaging and organoid bioprinting for biomedical research and therapeutic applications.Advanced drug delivery reviews · 2024Review
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Authors and funding
6 authors.
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Abstract
Intestinal epithelial organoids recapitulate many of the in vivo features of the intestinal epithelium, thus representing excellent research models. Morphology of the organoids based on light-microscopy images is used as a proxy to assess the biological state of the intestinal epithelium. Currently, organoid classification is manual and, therefore, subjective and time consuming, hampering large-scale quantitative analyses. Here, we describe Tellu, an object-detector algorithm trained to classify cultured intestinal organoids. Tellu was trained by manual annotation of >20,000 intestinal organoids to identify cystic non-budding organoids, early organoids, late organoids and spheroids. Tellu can also be used to quantify the relative organoid size, and can classify intestinal organoids into these four subclasses with accuracy comparable to that of trained scientists but is significantly faster and without bias. Tellu is provided as an open, user-friendly online tool to benefit the increasing number of investigations using organoids through fast and unbiased organoid morphology and size analysis.
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