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Patch-Based Directional Redundant Wavelets in Compressed Sensing Parallel Magnetic Resonance Imaging with Radial Sampling Trajectory

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Compressed sensing has been shown promising to speed up magnetic resonance imaging, and its combination with partially parallel imaging can further accelerate the data acquisition. For compressed sensing, a sparser representation of an image usually leads to lower reconstruction errors. Recently, a patch-based directional wavelets (PBDW), providing an adaptive sparse representation of image patches with geometric information, has been proposed in compressed sensing MRI to improve the edge reconstruction. However, it is still unknown how to incorporate PBDW into partially parallel imaging. In this work, we propose to use patch-based directional redundant wavelets (PBDRW) as an adaptive sparsifying transform in compressed sensing sensitivity encoding, and wed the new method with radial sampling to achieve higher acceleration factors. Results from simulation and in vivo data indicate that PBDRW in sensitivity encoding achieves lower reconstruction errors and preserves more image details than traditional total variation and wavelets.
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Keywords: COMPRESSED SENSING; MRI; PARALLEL IMAGING; RADIAL SAMPLING; WAVELETS

Document Type: Research Article

Publication date: 2016-04-01

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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