ArticleBMC bioinformatics2017
Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Universal consensus 3D segmentation of cells from 2D segmented stacks.Nature methods · 2025Article
- 3DCellComposer - A versatile pipeline utilizing 2D cell segmentation methods for 3D cell segmentation.Methods (San Diego, Calif.) · 2025Article
- Evaluation of cell segmentation methods without reference segmentations.Molecular biology of the cell · 2023Article
- Topological-Preserving Membrane Skeleton Segmentation in Multiplex Immunofluorescence Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- An assessment tool for computer-assisted semen analysis (CASA) algorithms.Scientific reports · 2022Article
- Automated high content image analysis of dendritic arborization in primary mouse hippocampal and rat cortical neurons in culture.Journal of neuroscience methods · 2020Article
- Automated classification of bacterial cell sub-populations with convolutional neural networks.PloS one · 2020Article
- Nessys: A new set of tools for the automated detection of nuclei within intact tissues and dense 3D cultures.PLoS biology · 2019Article
- Quantitating the Transfer of the HTLV-1 p8 Protein Between T-Cells by Flow Cytometry.Frontiers in microbiology · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundManual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines.
resultsWe present a new approach to simulate fluorescent cell micrographs that provides an objective ground truth for the validation of cell segmentation methods. The cell simulation was evaluated twofold: (1) An expert observer study shows that the proposed approach generates realistic fluorescent cell micrograph simulations. (2) An automated segmentation pipeline on the simulated fluorescent cell micrographs reproduces segmentation performances of that pipeline on real fluorescent cell micrographs.
conclusionThe proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.
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