Dose Super-Resolution in Prostate Volumetric Modulated Arc Therapy Using Cascaded Deep Learning Networks

Dose Super-Resolution in Prostate Volumetric Modulated Arc Therapy Using Cascaded Deep Learning Networks

PurposeThis study proposes a cascaded network model for generating high-resolution doses (i.e., a 1 mm grid) from low-resolution doses (i.e., ≥3 mm grids) with reduced computation time.MethodsUsing the anisotropic analytical algorithm with three grid sizes (1, 3, and 5 mm) and the Acuros XB algorith...

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Bibliographic Details
Main Authors: Dong-Seok Shin, Kyeong-Hyeon Kim, Sang-Won Kang, Seong-Hee Kang, Jae-Sung Kim, Tae-Ho Kim, Dong-Su Kim, Woong Cho, Tae Suk Suh, Jin-Beom Chung
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Oncology
Subjects:
deep learning
cascaded networks
dose super-resolution
dose grid size
prostate volumetric modulated arc therapy
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2020.593381/full

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https://www.frontiersin.org/articles/10.3389/fonc.2020.593381/full

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