ArticlePLoS computational biology2021
Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- Human organoids: Fit for drug discovery?Stem cell reports · 2026Review
- Label-free interferometry platform for drug response profiling of bioprinted tumor organoids at single-organoid resolution.Nature protocols · 2026Review
- Review
- High-content imaging of primary chronic lymphocytic leukemia cells predicts patient cohorts with distinct cellular drug responses.iScience · 2025Article
- Evolution of the PRNT: Merging tradition and innovation to set the gold standard in the era of automation.Human vaccines & immunotherapeutics · 2025Review
- A New Perspective on Precision Medicine: The Power of Digital Organoids.Biomaterials research · 2025Review
- Harnessing the power of artificial intelligence for human living organoid research.Bioactive materials · 2024Review
- Article
- Advancing cancer research through organoid technology.Journal of translational medicine · 2024Review
- Morphological profiling for drug discovery in the era of deep learning.Briefings in bioinformatics · 2024Review
- AI-organoid integrated systems for biomedical studies and applications.Bioengineering & translational medicine · 2024Review
- AI-enabled organoids: Construction, analysis, and application.Bioactive materials · 2024Review
- A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids.Cell systems · 2023Article
- Organoid Cultures In Silico: Tools or Toys?Bioengineering (Basel, Switzerland) · 2022Review
- Challenges and advances in optical 3D mesoscale imaging.Journal of microscopy · 2022Article
- Organoids.Nature reviews. Methods primers · 2022Article
- CODEX, a neural network approach to explore signaling dynamics landscapes.Molecular systems biology · 2021Article
- Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain.Frontiers in neuroanatomy · 2021Review
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Authors and funding
6 authors.
Funding
Abstract
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-to-segment images such as of neurons and organoids. Here we describe a comprehensive shallow-learning framework for automated quantitative phenotyping of three-dimensional (3D) image data using unsupervised data-driven voxel-based feature learning, which enables computationally facile classification, clustering and advanced data visualization. We demonstrate the analysis potential on complex 3D images by investigating the phenotypic alterations of: neurons in response to apoptosis-inducing treatments and morphogenesis for oncogene-expressing human mammary gland acinar organoids. Our novel implementation of image analysis algorithms called Phindr3D allowed rapid implementation of data-driven voxel-based feature learning into 3D high content analysis (HCA) operations and constitutes a major practical advance as the computed assignments represent the biology while preserving the heterogeneity of the underlying data. Phindr3D is provided as Matlab code and as a stand-alone program (https://github.com/DWALab/Phindr3D).
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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.