ArticleLight, science & applications2023
PhaseFIT: live-organoid phase-fluorescent image transformation via generative AI.
Article in Light, science & applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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
16 citing papers in PubMed, 25 citations in OpenAlex.
- Real-time sensing-integrated organoid-on-a-chip platforms: Technological progress and emerging biomedical applications.Bioactive materials · 2026Review
- Progress in the Design and Clinical Application of Probes for Fluorescence-Guided Laparoscopic Surgery.Chemical & biomedical imaging · 2026Review
- PAVSAT: an automated blood vessel analysis tool using deep learning-based segmentation and image processing.BMC bioinformatics · 2026Article
- Application of organoid models in basic and translational research of lung cancer: a narrative review.Translational lung cancer research · 2026Review
- Foundation model cascades enable zero-shot microscopy image analysis for cell therapy manufacturing.Cytotherapy · 2026Article
- Micro Pattern-Based 3D Cell Culture Platform: An Overview of Technologies and Applications.Exploration (Beijing, China) · 2026Review
- High-frequency energy fusion (HFEF) for nuclei segmentation with boundary-aware loss.Quantitative imaging in medicine and surgery · 2026Article
- Transformer-Based Deep Learning for Population-Scale Retinal Image Screening of Ophthalmic Disorders.Bioengineering (Basel, Switzerland) · 2026Article
- A Sensor-Oriented Multimodal Medical Data Acquisition and Modeling Framework for Tumor Grading and Treatment Response Analysis.Sensors (Basel, Switzerland) · 2026Article
- Generative Ai for Cardiovascular Cell Type-Specific Fluorescence Colorization of Live-Cell hPSC-Derived Cardiac Organoids.Advanced intelligent discovery · 2025Article
- Advancing Multicolor Super-Resolution Volume Imaging: Illuminating Complex Cellular Dynamics.JACS Au · 2025Review
- Large Context, Deeper Insights: Harnessing Large Language Models for Advancing Protein-Protein Interaction Analysis.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Deep Learning-Enabled Integration of Histology and Transcriptomics for Tissue Spatial Profile Analysis.Research (Washington, D.C.) · 2025Article
- Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy.Light, science & applications · 2024Review
- A systematic evaluation of computational methods for cell segmentation.bioRxiv : the preprint server for biology · 2024Article
- A systematic evaluation of computational methods for cell segmentation.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
Organoid models have provided a powerful platform for mechanistic investigations into fundamental biological processes involved in the development and function of organs. Despite the potential for image-based phenotypic quantification of organoids, their complex 3D structure, and the time-consuming and labor-intensive nature of immunofluorescent staining present significant challenges. In this work, we developed a virtual painting system, PhaseFIT (phase-fluorescent image transformation) utilizing customized and morphologically rich 2.5D intestinal organoids, which generate virtual fluorescent images for phenotypic quantification via accessible and low-cost organoid phase images. This system is driven by a novel segmentation-informed deep generative model that specializes in segmenting overlap and proximity between objects. The model enables an annotation-free digital transformation from phase-contrast to multi-channel fluorescent images. The virtual painting results of nuclei, secretory cell markers, and stem cells demonstrate that PhaseFIT outperforms the existing deep learning-based stain transformation models by generating fine-grained visual content. We further validated the efficiency and accuracy of PhaseFIT to quantify the impacts of three compounds on crypt formation, cell population, and cell stemness. PhaseFIT is the first deep learning-enabled virtual painting system focused on live organoids, enabling large-scale, informative, and efficient organoid phenotypic quantification. PhaseFIT would enable the use of organoids in high-throughput drug screening applications.
Identifiers
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.