DocumentCode
3535087
Title
Performance evaluation of iterative image reconstruction algorithms for non-sparse object reconstruction
Author
Singh, Santosh
Author_Institution
Siemens Corp. Technol. - India, Bangalore, India
fYear
2010
fDate
Oct. 30 2010-Nov. 6 2010
Firstpage
3245
Lastpage
3247
Abstract
Partially regularized technique is an extension based on interval constraint of minimum norm solution. Such techniques have shown good results on problems like Missing Data Recovery (MDR). The proposed use of partially regularized technique for the computer tomography (CT) image reconstruction is to investigate if the MDR concept can be used for few view projection data acquisition scenario. The motivation for such an implementation is to establish a concept of MDR in sparse CT image reconstruction. In the present initial conceptual work, the sparse CT image reconstruction means highly under-sampled data.
Keywords
computerised tomography; image reconstruction; iterative methods; medical image processing; computer tomography image reconstruction; highly undersampled data; iterative image reconstruction algorithms; minimum norm solution; missing data recovery; nonsparse object reconstruction; partially regularized technique; performance evaluation; projection data acquisition scenario; sparse CT image reconstruction; Computed tomography; Data acquisition; Equations; Image reconstruction; Mathematical model; Shape; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE
Conference_Location
Knoxville, TN
ISSN
1095-7863
Print_ISBN
978-1-4244-9106-3
Type
conf
DOI
10.1109/NSSMIC.2010.5874404
Filename
5874404
Link To Document