2024
DOI: 10.3389/fonc.2024.1433225
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Exploring the impact of network depth on 3D U-Net-based dose prediction for cervical cancer radiotherapy

Mingqing Wang,
Yuxi Pan,
Xile Zhang
et al.

Abstract: PurposeThe 3D U-Net deep neural network structure is widely employed for dose prediction in radiotherapy. However, the attention to the network depth and its impact on the accuracy and robustness of dose prediction remains inadequate.Methods92 cervical cancer patients who underwent Volumetric Modulated Arc Therapy (VMAT) are geometrically augmented to investigate the effects of network depth on dose prediction by training and testing three different 3D U-Net structures with depths of 3, 4, and 5.ResultsFor pla… Show more

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