A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion

A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion

Abstract Objectives Radiation-induced xerostomia is a common sequela in patients who undergo head and neck radiation therapy. This study aims to develop a three-dimensional deep learning model to predict xerostomia by fusing data from the gross tumor volume primary (GTVp) channel and parotid glands...

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Bibliographic Details
Main Authors: Lin Lin, Yuchen Ren, Wanwei Jian, Geng Yang, Bailin Zhang, Lin Zhu, Wenhao Zhao, Haoyu Meng, Xuetao Wang, Qiang He
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Imaging
Subjects:
Deep learning
Xerostomia
Decision fusion
Online Access:https://doi.org/10.1186/s12880-025-01848-1
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