Acceleration of MAP-EM algorithm via over-relaxation

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

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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 languageEnglish
Pages (from-to)100-107
Number of pages8
JournalComputerized Medical Imaging and Graphics
Publication statusPublished - 2015 Mar 1

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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