Detecting and quantifying spatial misalignment between longitudinal kilovoltage computed tomography (kVCT) scans of the head and neck by using convolutional neural networks (CNNs).
Fiche publication
Date publication
février 2023
Journal
Technology and health care : official journal of the European Society for Engineering and Medicine
Auteurs
Membres identifiés du Cancéropôle Est :
Pr ANTONI Delphine, Dr NOBLET Vincent
Tous les auteurs :
Lallement A, Noblet V, Antoni D, Meyer P
Lien Pubmed
Résumé
Adaptive radiotherapy (ART) aims to address anatomical modifications appearing during the treatment of patients by modifying the planning treatment according to the daily positioning image. Clinical implementation of ART relies on the quality of the deformable image registration (DIR) algorithms included in the ART workflow. To translate ART into clinical practice, automatic DIR assessment is needed.
Mots clés
DIR in radiotherapy, DIR validation, Registration error, adaptive radiotherapy, convolutional neural networks, deep learning, supervised learning
Référence
Technol Health Care. 2023 02 2;: