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A fast Edge‐preserving Bayesian reconstruction method for Parallel Imaging applications in cardiac MRI
Author(s) -
Singh Gurmeet,
Raj Ashish,
Kressler Bryan,
Nguyen Thanh D.,
Spincemaille Pascal,
Zabih Ramin,
Wang Yi
Publication year - 2011
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.22584
Subject(s) - computer science , sensitivity (control systems) , iterative reconstruction , image quality , artificial intelligence , algorithm , acceleration , reduction (mathematics) , peak signal to noise ratio , signal (programming language) , range (aeronautics) , encoding (memory) , computer vision , image (mathematics) , mathematics , physics , geometry , classical mechanics , electronic engineering , engineering , programming language , materials science , composite material
Among recent parallel MR imaging reconstruction advances, a Bayesian method called Edge‐preserving Parallel Imaging reconstructions with GRAph cuts Minimization (EPIGRAM) has been demonstrated to significantly improve signal‐to‐noise ratio when compared with conventional regularized sensitivity encoding method. However, EPIGRAM requires a large number of iterations in proportion to the number of intensity labels in the image, making it computationally expensive for high dynamic range images. The objective of this study is to develop a Fast EPIGRAM reconstruction based on the efficient binary jump move algorithm that provides a logarithmic reduction in reconstruction time while maintaining image quality. Preliminary in vivo validation of the proposed algorithm is presented for two‐dimensional cardiac cine MR imaging and three‐dimensional coronary MR angiography at acceleration factors of 2–4. Fast EPIGRAM was found to provide similar image quality to EPIGRAM and maintain the previously reported signal‐to‐noise ratio improvement over regularized sensitivity encoding method, while reducing EPIGRAM reconstruction time by 25–50 times. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.