Title
Statistical interior tomography.
Abstract
This paper presents a statistical interior tomography (SIT) approach making use of compressed sensing (CS) theory. With the projection data modeled by the Poisson distribution, an objective function with a total variation (TV) regularization term is formulated in the maximization of a posteriori (MAP) framework to solve the interior problem. An alternating minimization method is used to optimize the objective function with an initial image from the direct inversion of the truncated Hilbert transform. The proposed SIT approach is extensively evaluated with both numerical and real datasets. The results demonstrate that SIT is robust with respect to data noise and down-sampling, and has better resolution and less bias than its deterministic counterpart in the case of low count data.
Year
DOI
Venue
2011
10.1109/TMI.2011.2106161
IEEE Trans. Med. Imaging
Keywords
Field
DocType
computerised tomography,computed tomography (ct),sit approach,compressed sensing (cs),maximum likelihood estimation,objective function,total variation regularization term,statistical interior tomography,compressed sensing theory,map framework,maximization of a posteriori framework,interior tomography,statistical iterative reconstruction,maximum a posterior (map) reconstruction,truncated hilbert transform,medical image processing,hilbert transforms,radiation dose,image reconstruction,hilbert transform,computed tomography,minimization,poisson model,algorithm design and analysis,animal studies,total variation,algorithms,region of interest,iterative reconstruction,image quality,algorithm design,poisson distribution,computer simulation,tv,compressed sensing
Iterative reconstruction,Computer vision,Mathematical optimization,A priori and a posteriori,Regularization (mathematics),Count data,Artificial intelligence,Poisson distribution,Hilbert transform,Maximization,Mathematics,Compressed sensing
Journal
Volume
Issue
ISSN
30
5
1558-254X
Citations 
PageRank 
References 
5
0.55
19
Authors
6
Name
Order
Citations
PageRank
Qiong Xu1896.55
Xuanqin Mou2155272.38
Ge Wang31000142.51
Jered Sieren450.55
Eric A Hoffman589789.55
Hengyong Yu629335.54