| MAŠKA, Martin, Vladimír ULMAN, Pablo DELGADO-RODRIGUEZ, Estibaliz GÓMEZ-DE-MARISCAL, Tereza NEČASOVÁ, Fidel A Guerrero PEÑA, Tsang Ing REN, Elliot M MEYEROWITZ, Tim SCHERR, Katharina LÖFFLER, Ralf MIKUT, Tianqi GUO, Yin WANG, Jan P ALLEBACH, Rina BAO, Noor M AL-SHAKARJI, Gani RAHMON, Imad Eddine TOUBAL, Kannappan PALANIAPPAN, Filip LUX, Petr MATULA, Ko SUGAWARA, Klas E G MAGNUSSON, Layton AHO, Andrew R COHEN, Assaf ARBELLE, Tal BEN-HAIM, Tammy Riklin RAVIV, Fabian ISENSEE, Paul F JÄGER, Klaus H MAIER-HEIN, Yanming ZHU, Cristina EDERRA, Ainhoa URBIOLA, Erik MEIJERING, Alexandre CUNHA, Arrate MUÑOZ-BARRUTIA, Michal KOZUBEK and Carlos ORTIZ-DE-SOLÓRZANO. The Cell Tracking Challenge: 10 years of objective benchmarking. Nature Methods. 2023, vol. 20, No 7, p. 1010-1020. ISSN 1548-7091. Available from: https://dx.doi.org/10.1038/s41592-023-01879-y. |
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@article{2285029,
author = {Maška, Martin and Ulman, Vladimír and DelgadoandRodriguez, Pablo and GómezanddeandMariscal, Estibaliz and Nečasová, Tereza and Peña, Fidel A Guerrero and Ren, Tsang Ing and Meyerowitz, Elliot M and Scherr, Tim and Löffler, Katharina and Mikut, Ralf and Guo, Tianqi and Wang, Yin and Allebach, Jan P and Bao, Rina and AlandShakarji, Noor M and Rahmon, Gani and Toubal, Imad Eddine and Palaniappan, Kannappan and Lux, Filip and Matula, Petr and Sugawara, Ko and Magnusson, Klas E G and Aho, Layton and Cohen, Andrew R and Arbelle, Assaf and BenandHaim, Tal and Raviv, Tammy Riklin and Isensee, Fabian and Jäger, Paul F and MaierandHein, Klaus H and Zhu, Yanming and Ederra, Cristina and Urbiola, Ainhoa and Meijering, Erik and Cunha, Alexandre and MuñozandBarrutia, Arrate and Kozubek, Michal and OrtizanddeandSolórzano, Carlos},
article_number = {7},
doi = {http://dx.doi.org/10.1038/s41592-023-01879-y},
keywords = {cell segmentation;cell tracking;benchmarking},
language = {eng},
issn = {1548-7091},
journal = {Nature Methods},
title = {The Cell Tracking Challenge: 10 years of objective benchmarking},
url = {https://doi.org/10.1038/s41592-023-01879-y},
volume = {20},
year = {2023}
}
TY - JOUR
ID - 2285029
AU - Maška, Martin - Ulman, Vladimír - Delgado-Rodriguez, Pablo - Gómez-de-Mariscal, Estibaliz - Nečasová, Tereza - Peña, Fidel A Guerrero - Ren, Tsang Ing - Meyerowitz, Elliot M - Scherr, Tim - Löffler, Katharina - Mikut, Ralf - Guo, Tianqi - Wang, Yin - Allebach, Jan P - Bao, Rina - Al-Shakarji, Noor M - Rahmon, Gani - Toubal, Imad Eddine - Palaniappan, Kannappan - Lux, Filip - Matula, Petr - Sugawara, Ko - Magnusson, Klas E G - Aho, Layton - Cohen, Andrew R - Arbelle, Assaf - Ben-Haim, Tal - Raviv, Tammy Riklin - Isensee, Fabian - Jäger, Paul F - Maier-Hein, Klaus H - Zhu, Yanming - Ederra, Cristina - Urbiola, Ainhoa - Meijering, Erik - Cunha, Alexandre - Muñoz-Barrutia, Arrate - Kozubek, Michal - Ortiz-de-Solórzano, Carlos
PY - 2023
TI - The Cell Tracking Challenge: 10 years of objective benchmarking
JF - Nature Methods
VL - 20
IS - 7
SP - 1010-1020
EP - 1010-1020
SN - 15487091
KW - cell segmentation;cell tracking;benchmarking
UR - https://doi.org/10.1038/s41592-023-01879-y
N2 - 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.
ER -
MAŠKA, Martin, Vladimír ULMAN, Pablo DELGADO-RODRIGUEZ, Estibaliz GÓMEZ-DE-MARISCAL, Tereza NEČASOVÁ, Fidel A Guerrero PEÑA, Tsang Ing REN, Elliot M MEYEROWITZ, Tim SCHERR, Katharina LÖFFLER, Ralf MIKUT, Tianqi GUO, Yin WANG, Jan P ALLEBACH, Rina BAO, Noor M AL-SHAKARJI, Gani RAHMON, Imad Eddine TOUBAL, Kannappan PALANIAPPAN, Filip LUX, Petr MATULA, Ko SUGAWARA, Klas E G MAGNUSSON, Layton AHO, Andrew R COHEN, Assaf ARBELLE, Tal BEN-HAIM, Tammy Riklin RAVIV, Fabian ISENSEE, Paul F JÄGER, Klaus H MAIER-HEIN, Yanming ZHU, Cristina EDERRA, Ainhoa URBIOLA, Erik MEIJERING, Alexandre CUNHA, Arrate MUÑOZ-BARRUTIA, Michal KOZUBEK and Carlos ORTIZ-DE-SOLÓRZANO. The Cell Tracking Challenge: 10 years of objective benchmarking. \textit{Nature Methods}. 2023, vol.~20, No~7, p.~1010-1020. ISSN~1548-7091. Available from: https://dx.doi.org/10.1038/s41592-023-01879-y.
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