Bayesian penalized-likelihood reconstruction algorithm suppresses edge artifacts in PET reconstruction based on point-spread-function
作者: Shotaro YamaguchiKei WagatsumaKenta MiwaKenji IshiiKazumasa InoueMasahiro Fukushi
作者单位: 1Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
2Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
3School of Health Science, International University of Health and Welfare, Ohtawara, Japan
刊名: Physica Medica, 2018, Vol.47 , pp.73-79
来源数据库: Elsevier Journal
DOI: 10.1016/j.ejmp.2018.02.013
关键词: MAP-EMQuantificationContrastImage qualityArtifacts
英文摘要: Abstract(#br)Purpose(#br)The Bayesian penalized-likelihood reconstruction algorithm (BPL), Q.Clear, uses relative difference penalty as a regularization function to control image noise and the degree of edge-preservation in PET images. The present study aimed to determine the effects of suppression on edge artifacts due to point-spread-function (PSF) correction using a Q.Clear.(#br)Methods(#br)Spheres of a cylindrical phantom contained a background of 5.3 kBq/mL of [ 18 F]FDG and sphere-to-background ratios (SBR) of 16, 8, 4 and 2. The background also contained water and spheres containing 21.2 kBq/mL of [ 18 F]FDG as non-background. All data were acquired using a Discovery PET/CT 710 and were reconstructed using three-dimensional ordered-subset expectation maximization with...
全文获取路径: Elsevier  (合作)
影响因子:1.167 (2012)

  • reconstruction 复原
  • spread 散布
  • point 
  • algorithm 算法
  • likelihood 似然
  • MAP Aeronautical Maps And Charts
  • quality 品质
  • function 函数
  • based 基于
  • PET PagE frame Table