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

生物醫學工程學系

研究成果: Article › 同行評審

2 引文斯高帕斯（Scopus）

摘要

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.

原文	English
頁（從 - 到）	100-107
頁數	8
期刊	Computerized Medical Imaging and Graphics
卷	40
DOIs	https://doi.org/10.1016/j.compmedimag.2014.11.004
出版狀態	Published - 2015 3月 1

All Science Journal Classification (ASJC) codes

放射與超音波技術
放射學、核子醫學和影像學
電腦視覺和模式識別
健康資訊學
電腦繪圖與電腦輔助設計

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10.1016/j.compmedimag.2014.11.004

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@article{0985fd9fd55345cfbfd4885aeff2cfb9,

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.",

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

note = "Funding Information: This work was supported by Grants MOST 103-2314-B-182-010-MY3 from NSC , Taiwan, and CMRPD1C0641 , CMRPD1C0642 , CMRPD1C0671 , CMRPD1C0672 and CMRPD1C0382 from the Research Fund of Chang Gung Memorial Hospital, Taiwan . Conflict of interest statement Publisher Copyright: {\textcopyright} 2014 Elsevier Ltd.",

year = "2015",

month = mar,

day = "1",

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

language = "English",

volume = "40",

pages = "100--107",

journal = "Computerized Medical Imaging and Graphics",

issn = "0895-6111",

publisher = "Elsevier Limited",

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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

N1 - Funding Information: This work was supported by Grants MOST 103-2314-B-182-010-MY3 from NSC , Taiwan, and CMRPD1C0641 , CMRPD1C0642 , CMRPD1C0671 , CMRPD1C0672 and CMRPD1C0382 from the Research Fund of Chang Gung Memorial Hospital, Taiwan . Conflict of interest statement Publisher Copyright: © 2014 Elsevier Ltd.

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.

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DO - 10.1016/j.compmedimag.2014.11.004

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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

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