DocumentCode :
1910385
Title :
A generic statistical approach for emission computed tomography reconstruction
Author :
Ciurte, Anca ; Nedevschi, Sergiu ; Rasa, Ioan
Author_Institution :
Dept. of Comput. Sci., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear :
2013
fDate :
5-7 Sept. 2013
Firstpage :
77
Lastpage :
82
Abstract :
Nowadays nuclear imaging is increasingly used for non-invasive diagnosis. The image modalities in nuclear imaging suffer of worse statistics, in comparison with computed tomography, since they are based on emission transition tomography. Thus, precise reconstruction methods that can deal with incomplete or missing measurements are needed in order to improve the quality of nuclear images. In this paper we present a generalization of the state of the art EMML and ISRA algorithms for emission computed tomography reconstruction. The proposed method was tested and validated in comparison with the mentioned state of the art methods on a set of synthetic data. Better results (in terms of speed of convergence) were obtained for certain parameter settings.
Keywords :
computerised tomography; emission tomography; image reconstruction; radioisotope imaging; statistical analysis; EMML algorithms; ISRA algorithms; computed tomography; emission computed tomography reconstruction; emission transition tomography; generic statistical approach; noninvasive diagnosis; nuclear imaging; parameter settings; reconstruction methods; Computed tomography; Convergence; Detectors; Image reconstruction; Photonics; Positron emission tomography; Reconstruction algorithms; Expectation-Maximization Algorithm; Kullback-Leibler distances; image reconstruction; least-squares; linear systems; log-likelihood functions; positron emission tomography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computer Communication and Processing (ICCP), 2013 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4799-1493-7
Type :
conf
DOI :
10.1109/ICCP.2013.6646085
Filename :
6646085
Link To Document :
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