Evaluating Performance of a Deep Learning–based Artificial Intelligence Model for Ovarian Tumor Classification Using a Multicenter CT Dataset

Radiology Imaging Cancer 2026 Open access

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Authors: Anna H. Koch, Cris H. B. Claessens, Ingrid Nies, Eloy W.R. Schultz, Terese A. E. Hellström, Tim Boers, Eveline M. L. Dekker, Caroline L. P. Muntinga, J. S. van Evert, Ilse Niers-Stobbe, Annemarie Bruining, Christianne A. R. Lok
+3 more Joost Nederend, Fons van der Sommen, J.M.J. Piek
DOI: 10.1148/rycan.250027
Cited by: 1
References: 39

Abstract

A computer-aided diagnosis model for preoperative classification of ovarian tumors, developed using a multicenter CT dataset, demonstrated comparable performance to US-based models and radiologists on the internal and external test sets, illustrating challenges due to the heterogeneous nature of the disease and multicenter data.

Fields of Study & Subjects

Ovarian cancer diagnosis and treatment AI in cancer detection Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Radiology Imaging Cancer
Publisher
Radiological Society of North America (RSNA)
Volume
8
Issue
2
Pages
e250027–e250027
Publication date
13 February 2026
Language
EN