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,...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Medical image analysis Jg. 86; S. 102765
Hauptverfasser:	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
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.05.2023
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!