Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region

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Title		Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region
Authors		Arabi, Hossein Dowling, Jason A Burgos, Ninon Han, Xiao Greer, Peter B Koutsouvelis, Nikolaos Zaidi, Habib
Published in		Medical Physics. 2018, vol. 45, no. 11, p. 5218-5224
Abstract		Magnetic resonance imaging (MRI)-guided radiation therapy (RT) treatment planning is limited by the fact that the electron density distribution required for dose calculation is not readily provided by MR imaging. We compare a selection of novel synthetic CT generation algorithms recently reported in the literature, including segmentation-based, atlas-based and machine learning techniques, using the same cohort of patients and quantitative evaluation metrics.
Identifiers		DOI: 10.1002/mp.13187 PMID: 30216462
Full text		Article (Published version) (1.1 MB) - Free access
Structures		Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale
Research group		Imagerie Médicale (TEP et TEMP) (542)
Project		FNS: SNSF 320030_176052
Citation (ISO format)		ARABI, Hossein et al. Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region. In: Medical Physics, 2018, vol. 45, n° 11, p. 5218-5224. https://archive-ouverte.unige.ch/unige:110772