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Medical image reconstruction based on Bayesian compressed sensing

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5 Author(s)
Yu-Hong Li ; Shenzhen Inst. of Adv. Technol., Chinese Acad. of Sci., Shenzhen, China ; De-Feng Wang ; Lui, L.M. ; Ahuja, A.T.
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A medical image reconstruction method based on sparse Bayesian compressed sensing is presented, and the method employs a hierarchical model of the Laplace prior to model the sparse wavelet coefficients and unknown images. The experiments are designed to compare the Bayesian Compressed Sensing (BCS) method with the Basis Pursuit (BP) algorithm and the Orthogonal Matching Pursuit (OMP) algorithm. The results imply that the presented algorithm exceeds the greedy algorithm and the linear programming such as BP and OMP etc.

Published in:

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on  (Volume:4 )

Date of Conference:

10-13 July 2011