Accuracy of an articulated head-and-neck motion model using deep learning-based instance segmentation of skeletal bones in CT scans for image registration in radiotherapy

Accuracy of an articulated head-and-neck motion model using deep learning-based instance segmentation of skeletal bones in CT scans for image registration in radiotherapy

Knowing about anatomical deformations in patient images is crucial for adaptive image-guided radiation therapy. Biomechanical models ensure biofidelity in deformable image registration, but manual contouring limits their clinical use. We investigate the application of automatically generated contour...

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Bibliographic Details
Main Authors: Alexandra Walter, Cornelius J. Bauer, Ama Katseena Yawson, Philipp Hoegen-Saßmannshausen, Sebastian Adeberg, Jürgen Debus, Oliver Jäkel, Martin Frank, Kristina Giske
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
Subjects:
Biomechanical modelling
biofidelity
image registration
head and neck cancer
medical image segmentation
Online Access:https://www.tandfonline.com/doi/10.1080/21681163.2025.2455752

Internet

https://www.tandfonline.com/doi/10.1080/21681163.2025.2455752

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