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Abstract #2607

Fast Reconstruction of 3D LGE Images of the Left Atrium in a Compressed Sensing Framework Using Split Bregman

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

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Keywords

ablation acceleration accelerations achieved added adding applied arrows atrial atrium auxiliary chosen city clinical combined come compressed computationally computer conditioning constraint constraints consuming convergence cost dataset datasets degree degrees density descent dummy either electrical empirically enable encoding encodings engineering enhancement equivalent errors especially evaluate fast fibrillation fidelity formulation fully functional gadolinium gating good gradient gradients implemented inspection intensive internal inversion iterative jacket lake late learning like looked makes matrix measured medicine million minimization minimized minimizing minutes much navigator noise optimizing otherwise parallel patches patient patients people poor post problem problems process proposed quality radiology rapid reconstruct reconstructed reconstruction reconstructions recovery reduce reduces regularization regularized reported represent represents resolution respectively respiratory rule salt sampled sampling scheme schemes sensing sept similarity simulate slice slices slow solution solve space spatial split squared stack stars still suffer table takes term though toolbox traditional treatment truth unconstrained update valuable variable variables variation visible visual visualized wall