منابع مشابه
Blind Compressed Sensing Dynamic MRI
Introduction: Achieving high spatio-temporal resolutions in dynamic MRI (DMRI) (eg. myocardial perfusion MRI) is often challenging due to the slow nature of MR acquisitions. Recently, several schemes that exploit the low-rank property of dynamic datasets were introduced to accelerate dynamic MRI [eg: 1-3]. These methods exploit the similarity of the voxel time profiles (intensity variations as ...
متن کاملSparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.
PURPOSE To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. METHODS Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by...
متن کاملBlind Calibration in Compressed Sensing using Message Passing Algorithms
Compressed sensing (CS) is a concept that allows to acquire compressible signals with a small number of measurements. As such it is very attractive for hardware implementations. Therefore, correct calibration of the hardware is a central issue. In this paper we study the so-called blind calibration, i.e. when the training signals that are available to perform the calibration are sparse but unkn...
متن کاملSparse BLIP: Compressed Sensing with Blind Iterative Parallel Imaging
Huajun She, Rong-Rong Chen, Dong Liang, Edward DiBella, and Leslie Ying Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, United States, Shenzhen Institutes of Advanced Technology, Shenzhen, China, People's Republic of, Department of Electrical Engineering and Computer Science, University of Wisconsin, Milwaukee, WI, United States, Department of Radiol...
متن کاملAccelerated whole-brain multi-parameter mapping using blind compressed sensing.
PURPOSE To introduce a blind compressed sensing (BCS) framework to accelerate multi-parameter MR mapping, and demonstrate its feasibility in high-resolution, whole-brain T1ρ and T2 mapping. METHODS BCS models the evolution of magnetization at every pixel as a sparse linear combination of bases in a dictionary. Unlike compressed sensing, the dictionary and the sparse coefficients are jointly e...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2011
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2011.2165821