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 | |
| Publication status | Published - 2015 Mar 1 |
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All Science Journal Classification (ASJC) codes
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Graphics and Computer-Aided Design
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Acceleration of MAP-EM algorithm via over-relaxation. / Tsai, Yu Jung; Huang, Hsuan Ming; Fang, Yu-Hua Dean; Chang, Shi Ing; Hsiao, Ing Tsung.
In: Computerized Medical Imaging and Graphics, Vol. 40, 01.03.2015, p. 100-107.Research output: Contribution to journal › Article
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.
UR - http://www.scopus.com/inward/record.url?scp=84923044659&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84923044659&partnerID=8YFLogxK
U2 - 10.1016/j.compmedimag.2014.11.004
DO - 10.1016/j.compmedimag.2014.11.004
M3 - Article
C2 - 25465068
AN - SCOPUS:84923044659
VL - 40
SP - 100
EP - 107
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
SN - 0895-6111
ER -