2018
Why rankings of biomedical image analysis competitions should be interpreted with care
MAIER-HEIN, Lena, Matthias EISENMANN, Annika REINKE, Sinan ONOGUR, Marko STANKOVIC et. al.Základní údaje
Originální název
Why rankings of biomedical image analysis competitions should be interpreted with care
Autoři
MAIER-HEIN, Lena, Matthias EISENMANN, Annika REINKE, Sinan ONOGUR, Marko STANKOVIC, Patrick SCHOLZ, Tal ARBEL, Hrvoje BOGUNOVIC, Andrew BRADLEY, Aaron CARASS, Carolin FELDMANN, Alejandro FRANGI, Peter FULL, Bram VAN GINNEKEN, Allan HANBURY, Katrin HONAUER, Michal KOZUBEK (203 Česká republika, garant, domácí), Bennett LANDMAN, Keno MÄRZ, Oskar MAIER, Klaus MAIER-HEIN, Bjoern MENZE, Henning MÜLLER, Peter NEHER, Wiro NIESSEN, Nasir RAJPOOT, Gregory SHARP, Korsuk SIRINUKUNWATTANA, Stefanie SPEIDEL, Christian STOCK, Danail STOYANOV, Abdel Aziz TAHA, Fons VAN DER SOMMEN, Ching-Wei WANG, Marc-André WEBER, Guoyan ZHENG, Pierre JANNIN a Annette KOPP-SCHNEIDER
Vydání
Nature Communications, Nature Publishing Group, 2018, 2041-1723
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Švýcarsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 11.878
Kód RIV
RIV/00216224:14330/18:00101338
Organizační jednotka
Fakulta informatiky
UT WoS
000452282700012
Klíčová slova anglicky
biomedical image analysis; benchmarking; challenge
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 31. 12. 2018 08:54, RNDr. Pavel Šmerk, Ph.D.
Anotace
V originále
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future.
Návaznosti
GBP302/12/G157, projekt VaV |
| ||
LTC17016, projekt VaV |
|