@article{00a5cedfdc2d43e9a15daff6a3565921,
title = "Benchmark for multi-cellular segmentation of bright field microscopy images",
abstract = "Background: Multi-cellular segmentation of bright field microscopy images is an essential computational step when quantifying collective migration of cells in vitro. Despite the availability of various tools and algorithms, no publicly available benchmark has been proposed for evaluation and comparison between the different alternatives.Description: A uniform framework is presented to benchmark algorithms for multi-cellular segmentation in bright field microscopy images. A freely available set of 171 manually segmented images from diverse origins was partitioned into 8 datasets and evaluated on three leading designated tools.Conclusions: The presented benchmark resource for evaluating segmentation algorithms of bright field images is the first public annotated dataset for this purpose. This annotated dataset of diverse examples allows fair evaluations and comparisons of future segmentation methods. Scientists are encouraged to assess new algorithms on this benchmark, and to contribute additional annotated datasets.",
keywords = "Benchmarking, Collective cell migration, Segmentation, Wound healing assay",
author = "Assaf Zaritsky and Nathan Manor and Lior Wolf and Eshel Ben-Jacob and Ilan Tsarfaty",
note = "Funding Information: We are grateful to all colleagues who participated in data collection: Dr. Sivan Izraeli from Prof. Isaac P. Witz{\textquoteright}s laboratory, who acquired the “Melanoma” dataset; Prof. Petros Komoutsakos, who approved publication of the images available in the TScratch website as part of this benchmark (“TScratch” dataset); Sari Natan, Dr. Doron Kaplan and Yaniv Goikhman from Prof. Ilan Tsarfay{\textquoteright}s laboratory, who acquired the rest of the datasets. Doron Kaplan labeled regions of interest in the “MDCK” images. We thank Prof. Arieh Zaritsky for proofreading the manuscript. The work was supported in part by grants from the Breast Cancer Research Foundation; the Federico Foundation Grants; the US - Israel Binational Science Foundation and the Tauber Family Foundation at Tel Aviv University, the Center for Theoretical Biological Physics sponsored by the NSF (# PHY-0822283), and by the Cancer Prevention and Research Institute of Texas (CPRIT) at Rice University. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.",
year = "2013",
month = nov,
day = "7",
doi = "10.1186/1471-2105-14-319",
language = "אנגלית",
volume = "14",
journal = "BMC Bioinformatics",
issn = "1471-2105",
publisher = "BioMed Central Ltd.",
}