title: Improved signal-to-noise ratio in parallel coronary artery magnetic resonance angiography using graph cuts based Bayesian reconstruction.
abstract: High resolution 3D coronary artery MR angiography is time-consuming and can benefit from accelerated data acquisition provided by parallel imaging techniques without sacrificing spatial resolution. Currently, popular maximum likelihood based parallel imaging reconstruction techniques such as the SENSE algorithm offer this advantage at the cost of reduced signal-to-noise ratio (SNR). Maximum a posteriori (MAP) reconstruction techniques that incorporate globally smooth priors have been developed to recover this SNR loss, but they tend to blur sharp edges in the target image. The objective of this study is to demonstrate the feasibility of employing edge-preserving Markov random field priors in a MAP reconstruction framework, which can be solved efficiently using a graph cuts based optimization algorithm. The preliminary human study shows that our reconstruction provides significantly better SNR than the SENSE reconstruction performed by a commercially available scanner for navigator gated steady state free precession 3D coronary magnetic resonance angiography images (n = 4).
authors.affiliation: School of Electrical & Computer Engineering, Cornell University, Ithaca, NY, USA. gurmeet@cornell.edu
authors.forename: Gurmeet
authors.initials: G
authors.lastname: Singh
authors.forename: Thanh
authors.initials: T
authors.lastname: Nguyen
authors.forename: Bryan
authors.initials: B
authors.lastname: Kressler
authors.forename: Pascal
authors.initials: P
authors.lastname: Spincemaille
authors.forename: Ashish
authors.initials: A
authors.lastname: Raj
authors.forename: Ramin
authors.initials: R
authors.lastname: Zabih
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003331:Coronary Vessels / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity