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We present a new variational framework for recovery of apparent diffusion coefficient (ADC)from High Angular Resolution Diffusion-weighted (HARD) MRI. The model approximates the ADC profiles by a 4th order spherical harmonic series (SHS), whose coefficients are obtained by solving a constrained minimization problem. By minimizing the energy functional, the(More)
The application of Partially Parallel Imaging (PPI) techniques to regular clinical Magnetic Resonance Imaging (MRI) studies has brought about the benefit of significantly faster acquisitions but at the cost of amplified and spatially variant noise, especially, for high parallel imaging acceleration rates. A Local Mutual Information (LMI) weighted Total(More)
In the present study, a protocol was developed to obtain stable lines of the spring Dendrobium cv. ‘Sanya’ via Sonication-Assisted Agrobacterium-mediated Transformation (SAAT) of protocorm-like bodies (PLBs). Agrobacterium tumefaciens strain LBA4404 was used with the binary vector YF9078 containing the inverted repeat (IR) of ACC gene (IRACC) for the(More)
The method of enforcing sparsity during magnetic resonance imaging reconstruction has been successfully applied to partially parallel imaging (PPI) techniques to reduce noise and artifact levels and hence to achieve even higher acceleration factors. However, there are two major problems in the existing sparsity-constrained PPI techniques: speed and(More)
It is a challenging task to reconstruct images from their noisy, blurry, and/or incomplete measurements , especially those with important details and features such as medical magnetic resonance (MR) and CT images. We propose a novel regularization model that integrates two recently developed regularization tools: total generalized variation (TGV) by(More)
We present a variational framework for determination of intra-voxel fiber orientations from High Angular Resolution Diffusion-Weighted (HARD) MRI under the assumption of biGaussian diffusion. The approach is simultaneously estimating and regularizing the two tensor fields and the field of the proportionality corresponding to the mixture of two Gaussians.(More)
We propose EdgeCS — an edge guided compressive sensing reconstruction approach — to recover images of higher qualities from fewer measurements than the current state-of-the-art methods. Edges are important images features that are used in various ways in image recovery, analysis, and understanding. In compressive sensing, the sparsity of image edges has(More)
The relationship between brain structure and complex behavior is governed by large-scale neurocognitive networks. Diffusion weighted imaging(DWI) is a noninvasive technique that can visualize the neuronal projections connecting the functional centers and thus provides new keys to the understanding of brain function. In this paper, we assume there are up to(More)
We present a new approximation for the apparent diffusion coefficient (ADC) of non-Gaussian water diffusion with at most two fiber orientations within a voxel. The proposed model approximates ADC profiles by product of two spherical harmonic series (SHS) up to order 2 from High Angular Resolution Diffusion-weighted (HARD) MRI data. The coefficients of SHS(More)