Acceleration of MAP-EM algorithm via over-relaxation

Yu Jung Tsai; Hsuan Ming Huang; Yu Hua Dean Fang; Shi Ing Chang; Ing Tsung Hsiao

doi:10.1016/j.compmedimag.2014.11.004

Acceleration of MAP-EM algorithm via over-relaxation

Yu Jung Tsai, Hsuan Ming Huang, Yu Hua Dean Fang, Shi Ing Chang, Ing Tsung Hsiao^*

^*Corresponding author for this work

Chang Gung University

Research output: Contribution to journal › Journal Article › peer-review

2 Scopus citations

Abstract

To improve the convergence rate of the effective maximum a posteriori expectation-maximization (MAP-EM) algorithm in tomographic reconstructions, this study proposes a modified MAP-EM which uses an over-relaxation factor to accelerate image reconstruction. The proposed method, called MAP-AEM, is evaluated and compared with the results for MAP-EM and for an ordered-subset algorithm, in terms of the convergence rate and noise properties. The results show that the proposed method converges numerically much faster than MAP-EM and with a speed that is comparable to that for an ordered-subset type method. The proposed method is effective in accelerating MAP-EM tomographic reconstruction.

Original language	English
Pages (from-to)	100-107
Number of pages	8
Journal	Computerized Medical Imaging and Graphics
Volume	40
DOIs	https://doi.org/10.1016/j.compmedimag.2014.11.004
State	Published - 01 03 2015

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Ltd.

Keywords

Faster tomographic reconstruction
MAP-EM algorithm
PET reconstruction
SPECT reconstruction

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10.1016/j.compmedimag.2014.11.004

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title = "Acceleration of MAP-EM algorithm via over-relaxation",

abstract = "To improve the convergence rate of the effective maximum a posteriori expectation-maximization (MAP-EM) algorithm in tomographic reconstructions, this study proposes a modified MAP-EM which uses an over-relaxation factor to accelerate image reconstruction. The proposed method, called MAP-AEM, is evaluated and compared with the results for MAP-EM and for an ordered-subset algorithm, in terms of the convergence rate and noise properties. The results show that the proposed method converges numerically much faster than MAP-EM and with a speed that is comparable to that for an ordered-subset type method. The proposed method is effective in accelerating MAP-EM tomographic reconstruction.",

keywords = "Faster tomographic reconstruction, MAP-EM algorithm, PET reconstruction, SPECT reconstruction",

author = "Tsai, \{Yu Jung\} and Huang, \{Hsuan Ming\} and Fang, \{Yu Hua Dean\} and Chang, \{Shi Ing\} and Hsiao, \{Ing Tsung\}",

note = "Publisher Copyright: {\textcopyright} 2014 Elsevier Ltd.",

year = "2015",

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day = "1",

doi = "10.1016/j.compmedimag.2014.11.004",

language = "英语",

volume = "40",

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journal = "Computerized Medical Imaging and Graphics",

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TY - JOUR

T1 - Acceleration of MAP-EM algorithm via over-relaxation

AU - Tsai, Yu Jung

AU - Huang, Hsuan Ming

AU - Fang, Yu Hua Dean

AU - Chang, Shi Ing

AU - Hsiao, Ing Tsung

PY - 2015/3/1

Y1 - 2015/3/1

N2 - To improve the convergence rate of the effective maximum a posteriori expectation-maximization (MAP-EM) algorithm in tomographic reconstructions, this study proposes a modified MAP-EM which uses an over-relaxation factor to accelerate image reconstruction. The proposed method, called MAP-AEM, is evaluated and compared with the results for MAP-EM and for an ordered-subset algorithm, in terms of the convergence rate and noise properties. The results show that the proposed method converges numerically much faster than MAP-EM and with a speed that is comparable to that for an ordered-subset type method. The proposed method is effective in accelerating MAP-EM tomographic reconstruction.

AB - To improve the convergence rate of the effective maximum a posteriori expectation-maximization (MAP-EM) algorithm in tomographic reconstructions, this study proposes a modified MAP-EM which uses an over-relaxation factor to accelerate image reconstruction. The proposed method, called MAP-AEM, is evaluated and compared with the results for MAP-EM and for an ordered-subset algorithm, in terms of the convergence rate and noise properties. The results show that the proposed method converges numerically much faster than MAP-EM and with a speed that is comparable to that for an ordered-subset type method. The proposed method is effective in accelerating MAP-EM tomographic reconstruction.

KW - Faster tomographic reconstruction

KW - MAP-EM algorithm

KW - PET reconstruction

KW - SPECT reconstruction

UR - https://www.scopus.com/pages/publications/84923044659

U2 - 10.1016/j.compmedimag.2014.11.004

DO - 10.1016/j.compmedimag.2014.11.004

M3 - 文章

C2 - 25465068

AN - SCOPUS:84923044659

SN - 0895-6111

VL - 40

SP - 100

EP - 107

JO - Computerized Medical Imaging and Graphics

JF - Computerized Medical Imaging and Graphics

ER -

Acceleration of MAP-EM algorithm via over-relaxation

Abstract

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Keywords

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