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A benchmark for comparison of cell tracking algorithms

M. Maška, V. Ulman, D. Svoboda, P. Matula, P. Matula, C. Ederra, A. Urbiola, T. España, S. Venkatesan, DM. Balak, P. Karas, T. Bolcková, M. Streitová, C. Carthel, S. Coraluppi, N. Harder, K. Rohr, KE. Magnusson, J. Jaldén, HM. Blau, O....

. 2014 ; 30 (11) : 1609-17.

Language English Country England, Great Britain

Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, P.H.S.

Persistent link   https://www.medvik.cz/link/bmc14074282

MOTIVATION: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. RESULTS: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately. AVAILABILITY AND IMPLEMENTATION: The challenge Web site (http://www.codesolorzano.com/celltrackingchallenge) provides access to the training and competition datasets, along with the ground truth of the training videos. It also provides access to Windows and Linux executable files of the evaluation software and most of the algorithms that competed in the challenge.

Baxter Laboratory for Stem Cell Biology Department of Microbiology and Immunology Institute for Stem Cell Biology and Regenerative Medicine Stanford University School of Medicine Stanford CA 94305 USA

Biomedical Computer Vision Group Department of Bioinformatics and Functional Genomics University of Heidelberg BIOQUANT IPMB and DKFZ 69120 Heidelberg Germany

Biomedical Image Technologies Universidad Politécnica de Madrid and CIBER BBN 28040 Madrid Spain

Biomedical Imaging Group Rotterdam Erasmus University Medical Center 3015 GE Rotterdam The Netherlands

Cancer Imaging Laboratory Oncology Division Center for Applied Medical Research University of Navarra 31008 Pamplona Spain

Center for Biomedical Image Analysis Masaryk University 602 00 Brno Czech Republic

Center for Biomedical Image Analysis Masaryk University 602 00 Brno Czech Republic Biomedical Image Technologies Universidad Politécnica de Madrid and CIBER BBN 28040 Madrid Spain

Center for Biomedical Image Analysis Masaryk University 602 00 Brno Czech Republic Cancer Imaging Laboratory Oncology Division Center for Applied Medical Research University of Navarra 31008 Pamplona Spain

Division of Image Processing Leiden University Medical Center 2300 RC Leiden The Netherlands

Fusion Technology and Systems Department Compunetix Inc Monroeville PA 15146 USA

Institute of Cellular Biology and Pathology 1st Faculty of Medicine Charles University Prague 12801 Prague 2 Czech Republic

KTH Royal Institute of Technology ACCESS Linnaeus Center Department of Signal Processing 100 44 Stockholm Sweden

References provided by Crossref.org

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