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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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Principais autores: 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
Formato: Artigo
Idioma:Inglês
Publicado em: Elsevier 2021-02-01
Colecção:International Journal of Particle Therapy
Assuntos:
stopping power
dual-energy ct
proton therapy
machine learning
Acesso em linha:https://theijpt.org/doi/pdf/10.14338/IJPT-D-20-00020.1
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