Learning-Based Stopping Power Mapping on Dual-Energy CT for Proton Radiation Therapy

Learning-Based Stopping Power Mapping on Dual-Energy CT for Proton Radiation Therapy

Purpose: Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-base...

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Bibliographic Details
Main Authors: Tonghe Wang, PhD, Yang Lei, PhD, Joseph Harms, PhD, Beth Ghavidel, MS, Liyong Lin, PhD, Jonathan J. Beitler, MD, Mark McDonald, MD, Walter J. Curran, MD, Tian Liu, PhD, Jun Zhou, PhD, Xiaofeng Yang, PhD
Format: Article
Language:English
Published: Particle Therapy Co-operative Group 2021-02-01
Series:International Journal of Particle Therapy
Subjects:
stopping power
dual-energy ct
proton therapy
machine learning
Online Access:https://theijpt.org/doi/pdf/10.14338/IJPT-D-20-00020.1

Internet

https://theijpt.org/doi/pdf/10.14338/IJPT-D-20-00020.1

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