Srikant Kamesh Iyer1,
2, Tolga Tasdizen3, Nathan Burgon4, Ganesh Adluru2,
Edward V.R. DiBella2
1Electrical
and Computer Engineering, University of Utah, Salt Lake City, UT, United
States; 2UCAIR/Radiology, University of Utah, Salt Lake City, UT,
United States; 3SCI, University of Utah, Salt Lake City, Salt Lake
City, UT, United States; 4CARMA, Department of Internal Medicine,
University of Utah, Salt Lake City, Salt Lake City, UT, United States
Acquiring Late Gadolinium Enhanced (LGE) images of the left atrium is a valuable tool in assessing the degree of fibrosis in the left atrium. The current method of acquiring high resolution 3D Cartesian inversion recovery data with ECG gating and respiratory navigator is inherently time consuming. Advances in compressed sensing have made it possible to speed up acquisition by acquiring less data while maintaining image quality by using prior information about the underlying image as constraints in the reconstruction. Total variation is one such popular constraint used. The nonlinearity and poor conditioning of such L1 regularization based reconstruction schemes makes minimization using traditional schemes like gradient descent very slow. We propose to use the Split Bregman approach to reconstruct LGE images of the LA in a compressed sensing framework to achieve rapid reconstructions for high acceleration factors