Title :
Performance evaluation of iterative image reconstruction algorithms for non-sparse object reconstruction
Author_Institution :
Siemens Corp. Technol. - India, Bangalore, India
fDate :
Oct. 30 2010-Nov. 6 2010
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;
Conference_Titel :
Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE
Conference_Location :
Knoxville, TN
Print_ISBN :
978-1-4244-9106-3
DOI :
10.1109/NSSMIC.2010.5874404