Edward V. R. Di Bella

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We introduce a novel algorithm to reconstruct dynamic magnetic resonance imaging (MRI) data from under-sampled k-t space data. In contrast to classical model based cine MRI schemes that rely on the sparsity or banded structure in Fourier space, we use the compact representation of the data in the Karhunen Louve transform (KLT) domain to exploit the(More)
Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the(More)
Routinely trade-offs between the spatio-temporal resolution, volume coverage and SNR are done in first pass cardiac perfusion MRI due to the restricted imaging acquisition window (usually of the order of 300 to 400 msec per heart beat). In this paper, we demonstrate the use a low rank and sparse reconstruction scheme (k − t SLR) in obtaining highly(More)
Diffusion magnetic resonance imaging (dMRI) is the modality of choice for investigating in-vivo white matter connectivity and neural tissue architecture of the brain. The diffusion-weighted signal in dMRI reflects the diffusivity of water molecules in brain tissue and can be utilized to produce image-based biomarkers for clinical research. Due to the(More)
The objective of this study was to validate a deformable image registration technique, termed Hyperelastic Warping, for left ventricular strain measurement during systole using cine-gated, non-tagged MR images with strains measured from tagged MRI. The technique combines deformation from high resolution, non-tagged MR image data with a detailed(More)
Segmentation of the myocardium in dynamic contrast enhanced MR short axis images is an important step towards the estimation of semi-quantitative or quantitative parameters to determine the perfusion to the tissue regions. The perfusion indices of the tissue are obtained by dividing the tissue into regions of interest and estimating perfusion to each(More)
Recently, there has been a significant interest in applying reconstruction techniques, like constrained reconstruction or compressed sampling methods, to undersampled k-space data in MRI. Here, we propose a novel reordering technique to improve these types of reconstruction methods. In this technique, the intensities of the signal estimate are reordered(More)
Motion of the heart has complicated in vivo applications of cardiac diffusion MRI and diffusion tensor imaging (DTI), especially in small animals such as rats where ultra-high-performance gradient sets are currently not available. Even with velocity compensation via, for example, bipolar encoding pulses, the variable shot-to-shot residual motion-induced(More)