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Model-Based Image Reconstruction for Dynamic Cardiac Perfusion MRI from Sparse Data

Model-Based Image Reconstruction for Dynamic Cardiac Perfusion MRI from Sparse Data,10.1109/IEMBS.2006.260363,Suyash P. Awate,Edward V. R. DiBella,Tol

Model-Based Image Reconstruction for Dynamic Cardiac Perfusion MRI from Sparse Data   (Citations: 2)
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The paper presents a novel approach for dynamic magnetic resonance imaging (MRI) cardiac perfusion image reconstruction from sparse k-space data. It formulates the reconstruction problem in an inverse-methods setting. Relevant prior information is incorporated via a parametric model for the perfusion process. This wealth of prior information empowers the proposed method to give high-quality reconstructions from very sparse k-space data. The paper presents reconstruction results using both Cartesian and radial sampling strategies using data simulated from a real acquisition. The proposed method produces high-quality reconstructions using 14% of the k-space data. The model-based approach can potentially greatly benefit cardiac myocardial perfusion studies as well as other dynamic contrast-enhanced MRI applications including tumor imaging
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