Design and evaluation of a deep learning-based automatic segmentation of maxillary and mandibular substructures using a 3D U-Net

Design and evaluation of a deep learning-based automatic segmentation of maxillary and mandibular substructures using a 3D U-Net

Background: Current segmentation approaches for radiation treatment planning in head and neck cancer patients (HNCP) typically consider the entire mandible as an organ at risk, whereas segmentation of the maxilla remains uncommon. Accurate risk assessment for osteoradionecrosis (ORN) or implant-base...

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Bibliographic Details
Main Authors: L. Melerowitz, S. Sreenivasa, M. Nachbar, A. Stsefanenka, M. Beck, C. Senger, N. Predescu, S. Ullah Akram, V. Budach, D. Zips, M. Heiland, S. Nahles, C. Stromberger
Format: Article
Language:English
Published: Elsevier 2024-07-01
Series:Clinical and Translational Radiation Oncology
Subjects:
Jaw
Dental rehabilitation
Osteoradionecrosis
Radiation therapy
Artificial intelligence
Head and neck cancer
Online Access:http://www.sciencedirect.com/science/article/pii/S2405630824000570

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http://www.sciencedirect.com/science/article/pii/S2405630824000570

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