Beyond rankings: Learning (more) from algorithm validation

Challenges have become the state-of-the-art approach to benchmark image analysis algorithms in a comparative manner. While the validation on identical data sets was a great step forward, results analysis is often restricted to pure ranking tables, leaving relevant questions unanswered. Specifically,...

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Vydáno v:	Medical image analysis Ročník 86; s. 102765
Hlavní autoři:	Roß, Tobias, Bruno, Pierangela, Reinke, Annika, Wiesenfarth, Manuel, Koeppel, Lisa, Full, Peter M., Pekdemir, Bünyamin, Godau, Patrick, Trofimova, Darya, Isensee, Fabian, Adler, Tim J., Tran, Thuy N., Moccia, Sara, Calimeri, Francesco, Müller-Stich, Beat P., Kopp-Schneider, Annette, Maier-Hein, Lena
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.05.2023
Témata:	Algorithms Artificial intelligence Biomedical image analysis challenges Deep learning Endoscopic vision Generalized linear mixed models Grand challenges Humans Image characteristics driven algorithm development Image Processing, Computer-Assisted - methods Instrument segmentation Laparoscopy Minimally invasive surgery Surgical data science Deep learning Minimally invasive surgery Generalized linear mixed models Image characteristics driven algorithm development Grand challenges Biomedical image analysis challenges Surgical data science Artificial intelligence Instrument segmentation Endoscopic vision
ISSN:	1361-8415, 1361-8423, 1361-8423
On-line přístup:	Získat plný text
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