دورية أكاديمية
The Cell Tracking Challenge: 10 years of objective benchmarking.
| العنوان: | The Cell Tracking Challenge: 10 years of objective benchmarking. |
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| المؤلفون: | Maška M; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic., Ulman V; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic.; IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava, Ostrava, Czech Republic., Delgado-Rodriguez P; Bioengineering Department, Universidad Carlos III de Madrid, Madrid, Spain.; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain., Gómez-de-Mariscal E; Bioengineering Department, Universidad Carlos III de Madrid, Madrid, Spain.; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.; Optical Cell Biology, Instituto Gulbenkian de Ciência, Oeiras, Portugal., Nečasová T; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic., Guerrero Peña FA; Centro de Informatica, Universidade Federal de Pernambuco, Recife, Brazil.; Center for Advanced Methods in Biological Image Analysis, Beckman Institute, California Institute of Technology, Pasadena, CA, USA., Ren TI; Centro de Informatica, Universidade Federal de Pernambuco, Recife, Brazil., Meyerowitz EM; Division of Biology and Biological Engineering and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA, USA., Scherr T; Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany., Löffler K; Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany., Mikut R; Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany., Guo T; The Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA., Wang Y; The Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA., Allebach JP; The Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA., Bao R; Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.; CIVA Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA., Al-Shakarji NM; CIVA Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA., Rahmon G; CIVA Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA., Toubal IE; CIVA Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA., Palaniappan K; CIVA Lab, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA., Lux F; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic., Matula P; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic., Sugawara K; Institut de Génomique Fonctionnelle de Lyon (IGFL), École Normale Supérieure de Lyon, Lyon, France.; Centre National de la Recherche Scientifique (CNRS), Paris, France., Magnusson KEG; Raysearch Laboratories AB, Stockholm, Sweden., Aho L; Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA., Cohen AR; Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA., Arbelle A; School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beersheba, Israel., Ben-Haim T; School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beersheba, Israel., Raviv TR; School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beersheba, Israel., Isensee F; Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany., Jäger PF; Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Interactive Machine Learning Group, German Cancer Research Center (DKFZ), Heidelberg, Germany., Maier-Hein KH; Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany., Zhu Y; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia.; Griffith University, Nathan, Queensland, Australia., Ederra C; Biomedical Engineering Program and Ciberonc, Center for Applied Medical Research, Universidad de Navarra, Pamplona, Spain., Urbiola A; Biomedical Engineering Program and Ciberonc, Center for Applied Medical Research, Universidad de Navarra, Pamplona, Spain., Meijering E; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia., Cunha A; Center for Advanced Methods in Biological Image Analysis, Beckman Institute, California Institute of Technology, Pasadena, CA, USA., Muñoz-Barrutia A; Bioengineering Department, Universidad Carlos III de Madrid, Madrid, Spain.; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain., Kozubek M; Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic. kozubek@fi.muni.cz., Ortiz-de-Solórzano C; Biomedical Engineering Program and Ciberonc, Center for Applied Medical Research, Universidad de Navarra, Pamplona, Spain. codesolorzano@unav.es. |
| المصدر: | Nature methods [Nat Methods] 2023 Jul; Vol. 20 (7), pp. 1010-1020. Date of Electronic Publication: 2023 May 18. |
| نوع المنشور: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: New York, NY : Nature Pub. Group, c2004- |
| مواضيع طبية MeSH: | Benchmarking* , Cell Tracking*/methods, Machine Learning ; Algorithms |
| مستخلص: | The Cell Tracking Challenge is an ongoing benchmarking initiative that has become a reference in cell segmentation and tracking algorithm development. Here, we present a significant number of improvements introduced in the challenge since our 2017 report. These include the creation of a new segmentation-only benchmark, the enrichment of the dataset repository with new datasets that increase its diversity and complexity, and the creation of a silver standard reference corpus based on the most competitive results, which will be of particular interest for data-hungry deep learning-based strategies. Furthermore, we present the up-to-date cell segmentation and tracking leaderboards, an in-depth analysis of the relationship between the performance of the state-of-the-art methods and the properties of the datasets and annotations, and two novel, insightful studies about the generalizability and the reusability of top-performing methods. These studies provide critical practical conclusions for both developers and users of traditional and machine learning-based cell segmentation and tracking algorithms. (© 2023. The Author(s).) |
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| معلومات مُعتمدة: | R01 NS110915 United States NS NINDS NIH HHS; United States HHMI Howard Hughes Medical Institute |
| تواريخ الأحداث: | Date Created: 20230518 Date Completed: 20230712 Latest Revision: 20230801 |
| رمز التحديث: | 20230802 |
| مُعرف محوري في PubMed: | PMC10333123 |
| DOI: | 10.1038/s41592-023-01879-y |
| PMID: | 37202537 |
| قاعدة البيانات: | MEDLINE |
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Full Text Finder | تدمد: | 1548-7105 |
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| DOI: | 10.1038/s41592-023-01879-y |