A comparison of RIGR and SVD dynamic imaging methods

被引:10
作者
Hanson, JM
Liang, ZP
Magin, RL
Duerk, JL
Lauterbur, PC
机构
[1] UNIV ILLINOIS, BECKMAN INST ADV SCI & TECHNOL, URBANA, IL 61801 USA
[2] CASE WESTERN RESERVE UNIV, DEPT RADIOL, CLEVELAND, OH 44106 USA
[3] CASE WESTERN RESERVE UNIV, DEPT BIOMED ENGN, CLEVELAND, OH 44106 USA
关键词
dynamic imaging; fast imaging; image reconstruction; generalized series;
D O I
10.1002/mrm.1910380122
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Several constrained imaging methods have recently been proposed for dynamic imaging applications. This paper compares two of these methods: the Reduced-encoding imaging by Generalized-series Reconstruction (RIGR) and Singular Value Decomposition (SVD) methods. RIGR utilizes a priori data for optimal image reconstruction whereas the SVD method seeks to optimize data acquisition. However, this study shows that the existing SVD encoding method tends to bias the data acquisition scheme toward reproducing the known features in the reference image. This characteristic of the SVD encoding method reduces its capability to capture new image features and makes it less suitable than RIGR for dynamic imaging applications.
引用
收藏
页码:161 / 167
页数:7
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