DocumentCode
451740
Title
Derivation and implementation of ordered-subsets algorithms for list-mode PET data
Author
Nakayama, Takayuki ; Kudo, Hiroyuki
Author_Institution
Graduate Sch. of Syst. & Information Eng., Tsukuba Univ., Ibaraki, Japan
Volume
4
fYear
2005
fDate
23-29 Oct. 2005
Abstract
In this paper, we present a new derivation of a wide class of list-mode ordered-subsets (OS) algorithms for image reconstruction in PET. The derivation starts from the list-mode likelihood and follows the similar line to the block-gradient method for minimizing a general cost function. This derivation clarifies that there exist list-mode OS algorithms which behave significantly better than current standard list-mode OS-EM.
Keywords
gradient methods; image reconstruction; medical image processing; positron emission tomography; block-gradient method; general cost function; image reconstruction; list-mode PET data; list-mode likelihood; ordered-subsets algorithms; Cost function; Detectors; Event detection; Histograms; Image reconstruction; Iterative algorithms; Limit-cycles; Performance evaluation; Positron emission tomography; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Nuclear Science Symposium Conference Record, 2005 IEEE
ISSN
1095-7863
Print_ISBN
0-7803-9221-3
Type
conf
DOI
10.1109/NSSMIC.2005.1596714
Filename
1596714
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