ArticleScientific reports2019
Automated Segmentation of Fluorescence Microscopy Images for 3D Cell Detection in human-derived Cardiospheres.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prevalence and practices of immunofluorescent cell image processing: a systematic review.Frontiers in cellular neuroscience · 2023Pooled it
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- Organoids in drug development: from predictive models to regulatory integration.Drug discovery today · 2026Review
- Blockade of YAP Mechanoactivation Prevents Neointima Formation and Adverse Remodeling in Arterialized Vein Grafts.Journal of the American Heart Association · 2025Article
- Enhanced stem cell image segmentation by leveraging visual processing mechanisms.Frontiers in bioengineering and biotechnology · 2025Article
- Harnessing 3D cell models and high-resolution imaging to unveil the mechanisms of nanoparticle-mediated drug delivery.Frontiers in bioengineering and biotechnology · 2025Review
- Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images.Computers in biology and medicine · 2024Article
- Comparing Deep Learning Performance for Chronic Lymphocytic Leukaemia Cell Segmentation in Brightfield Microscopy Images.Bioinformatics and biology insights · 2024Article
- Dopamine-mediated striatal activity and function is enhanced in GlyRα2 knockout animals.iScience · 2023Article
- Cardiac fibroblasts and mechanosensation in heart development, health and disease.Nature reviews. Cardiology · 2023Review
- Volumetric imaging of human mesenchymal stem cells (hMSCs) for non-destructive quantification of 3D cell culture growth.PloS one · 2023Article
- POSEA: A novel algorithm to evaluate the performance of multi-object instance image segmentation.PloS one · 2023Article
- A comprehensive review of computational and image analysis techniques for quantitative evaluation of striated muscle tissue architecture.Biophysics reviews · 2022Review
- Article
- Automated Cell Foreground-Background Segmentation with Phase-Contrast Microscopy Images: An Alternative to Machine Learning Segmentation Methods with Small-Scale Data.Bioengineering (Basel, Switzerland) · 2022Article
- Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos Using Convolutional Neural Networks.IEEE access : practical innovations, open solutions · 2022Article
- Automated image segmentation method to analyse skeletal muscle cross section in exercise-induced regenerating myofibers.Scientific reports · 2021Article
- Viability fingerprint of glioblastoma cell lines: roles of mitotic, proliferative, and epigenetic targets.Scientific reports · 2021Article
- Image-Based Method to Quantify Decellularization of Tissue Sections.International journal of molecular sciences · 2021Article
- Cell segmentation-free inference of cell types from in situ transcriptomics data.Nature communications · 2021Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 'cardiosphere' is a 3D cluster of cardiac progenitor cells recapitulating a stem cell niche-like microenvironment with a potential for disease and regeneration modelling of the failing human myocardium. In this multicellular 3D context, it is extremely important to decrypt the spatial distribution of cell markers for dissecting the evolution of cellular phenotypes by direct quantification of fluorescent signals in confocal microscopy. In this study, we present a fully automated method, named CARE ('CARdiosphere Evaluation'), for the segmentation of membranes and cell nuclei in human-derived cardiospheres. The proposed method is tested on twenty 3D-stacks of cardiospheres, for a total of 1160 images. Automatic results are compared with manual annotations and two open-source software designed for fluorescence microscopy. CARE performance was excellent in cardiospheres membrane segmentation and, in cell nuclei detection, the algorithm achieved the same performance as two expert operators. To the best of our knowledge, CARE is the first fully automated algorithm for segmentation inside in vitro 3D cell spheroids, including cardiospheres. The proposed approach will provide, in the future, automated quantitative analysis of markers distribution within the cardiac niche-like environment, enabling predictive associations between cell mechanical stresses and dynamic phenotypic changes.
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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.