Open access
Sep 2026
Interpretable graph-conditioned CNNs for dose-volume histogram prediction in radiotherapy.
A novel deep learning framework that directly predicts full DVHs for multiple organs-at-risk (OARs) from computed tomography (CT) and structure contours and a graph neural network (GNN) that models each DVH as a structured graph, enabling sequential dose-volume dependencies to be learned explicitly.
Xiao-Ling Zhu, C. Ling, Hao Xu et al.
· Medical Physics (Lancaster) · 0 citations