Journal article
Statistical Interior Tomography
IEEE transactions on medical imaging, Vol.30(5), pp.1116-1128
05/2011
DOI: 10.1109/TMI.2011.2106161
PMCID: PMC3246757
PMID: 21233044
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.
Details
- Title: Subtitle
- Statistical Interior Tomography
- Creators
- Qiong Xu - Inst. of Image Process. & Pattern Recognition, Xi'an Jiaotong Univ., Xi'an, ChinaXuanqin Mou - Inst. of Image Process. & Pattern Recognition, Xi'an Jiaotong Univ., Xi'an, ChinaGe Wang - Biomed. Imaging Div., VT-WFU Sch. of Biomed. Eng. & Sci., Blacksburg, VA, USAJered Sieren - Dept. of Radiol., Univ. of Iowa, Iowa City, IA, USAEric A Hoffman - Dept. of Radiol., Univ. of Iowa, Iowa City, IA, USAHengyong Yu - Biomed. Imaging Div., VT-WFU Sch. of Biomed. Eng. & Sci., Blacksburg, VA, USA
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.30(5), pp.1116-1128
- Publisher
- IEEE
- DOI
- 10.1109/TMI.2011.2106161
- PMID
- 21233044
- PMCID
- PMC3246757
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Language
- English
- Date published
- 05/2011
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
- Record Identifier
- 9984051538502771
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