Fiche publication
Date publication
janvier 2025
Journal
International journal of gynecological cancer : official journal of the International Gynecological Cancer Society
Auteurs
Membres identifiés du Cancéropôle Est :
Pr AKLADIOS Chérif
Tous les auteurs :
Lecointre L, Alekseenko J, Pavone M, Karargyris A, Fanfani F, Fagotti A, Scambia G, Querleu D, Akladios C, Dana J, Padoy N
Lien Pubmed
Résumé
Evaluation of prognostic factors is crucial in patients with endometrial cancer for optimal treatment planning and prognosis assessment. This study proposes a deep learning pipeline for tumor and uterus segmentation from magnetic resonance imaging (MRI) images to predict deep myometrial invasion and cervical stroma invasion and thus assist clinicians in pre-operative workups.
Mots clés
Artificial Intelligence, Deep Learning, Digital Surgery, Endometrial Cancer, Image-guided Surgery
Référence
Int J Gynecol Cancer. 2025 01;35(1):100017
