Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Journal: Pediatric radiology

Published Date: Mar 1, 2016

BACKGROUND: CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT.

Young Jin Ryu

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
Young Hun Choi

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea. iater@snu.ac.kr.
Jung-Eun Cheon

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
Seongmin Ha

Institute of Biomedical Engineering Research, Kyungpook National University, 680, Gukchaebosang-ro, Jung-gu, Daegu 41944, Korea.
Woo Sun Kim

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.
In-One Kim

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea.

Child, Preschool Computer Simulation Female Humans Knowledge Bases Machine Learning Male Models, Statistical Phantoms, Imaging Radiation Dosage Radiation Exposure Radiation Protection Radiographic Image Enhancement Reproducibility of Results Sensitivity and Specificity Subtraction Technique Tomography, X-Ray Computed

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