Improving Image Quality of Cone-Beam CT Using Alternating Regression Forest

We propose a CBCT image quality improvement method based on anatomic signature and auto-context alternating regression forest. Patient-specific anatomical features are extracted from the aligned training images and served as signatures for each voxel. The most relevant and informative features are i...

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Detalles Bibliográficos
Publicado en:Proc SPIE Int Soc Opt Eng
Main Authors: Lei, Yang, Tang, Xiangyang, Higgins, Kristin, Wang, Tonghe, Liu, Tian, Dhabaan, Anees, Shim, Hyunsuk, Curran, Walter J., Yang, Xiaofeng
Formato: Artigo
Idioma:Inglês
Publicado: 2018
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Article
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC6711599/
https://ncbi.nlm.nih.gov/pubmed/31456600
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2292886
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