ArticleBiotechnology and bioengineering2014
Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images.
Article in Biotechnology and bioengineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
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- Segmentation-Free Multi-Fractal and Radiomics Response Profiling of Live Unstained Confluent Microglia In Vitro Using Phase-Contrast Microscopy Images.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Novel Drug-Testing Platform for Vascular Injury-induced Intimal Hyperplasia Using a Microphysiological System.Advanced healthcare materials · 2025Article
- AI-Driven Quality Monitoring and Control in Stem Cell Cultures: A Comprehensive Review.Biotechnology journal · 2025Review
- Compensating the Meniscus Effect in Phase Contrast Microscopy Using an LCD for Adaptive Condenser Annulus Shifting.Microscopy research and technique · 2025Article
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- Advancing cell therapy manufacturing: an image-based solution for accurate confluency estimation.Frontiers in bioengineering and biotechnology · 2025Article
- Single cell autofluorescence imaging reveals immediate metabolic shifts of neutrophils with activation across biological systems.Frontiers in immunology · 2025Article
- TR-107, an Agonist of Caseinolytic Peptidase Proteolytic Subunit, Disrupts Mitochondrial Metabolism and Inhibits the Growth of Human Colorectal Cancer Cells.Molecular cancer therapeutics · 2024Article
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- Spatial heterogeneity analysis of seeding of human induced pluripotent stem cells for neuroectodermal differentiation.Regenerative therapy · 2024Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license.
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Registered trials
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