An approach to positron emission tomography based on penalized cross-entropy minimization

We describe an approach to positron emission tomography, which aims to minimize the cross-entropy between the detected photon coincidence counts and the projection due to image vector, subject to the almost conservation in total tube counts and nonnegativity constraints. We derive formally a fixed p...

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Bibliographic Details
Published inSignal processing Vol. 81; no. 5; pp. 1069 - 1074
Main Authors Zhang, Song, Wang, Yuan Mei
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.05.2001
Elsevier Science
Subjects
Applied sciences
Cross-entropy
EM algorithm
Exact sciences and technology
Image processing
Information, signal and communications theory
Merit function
Positron emission tomography
Signal processing
Telecommunications and information theory
Positron emission tomography
EM algorithm
Merit function
Cross-entropy
Performance evaluation
Simulation
Iterative method
Kuhn Tucker condition
Minimum entropy methods
Maximum likelihood
Optimization
Image reconstruction
Online AccessGet full text
ISSN0165-1684
1872-7557
DOI10.1016/S0165-1684(00)00245-0

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Summary:We describe an approach to positron emission tomography, which aims to minimize the cross-entropy between the detected photon coincidence counts and the projection due to image vector, subject to the almost conservation in total tube counts and nonnegativity constraints. We derive formally a fixed point iterative algorithm to solve the corresponding optimization problem. The algorithm is applied to both simulated data based on a Shepp–Logan phantom and real data, and compared with some standard algorithms, the results demonstrating its effectiveness.
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ISSN:0165-1684
1872-7557
DOI:10.1016/S0165-1684(00)00245-0