Mariappan S. Nadar

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We present a method for stochastic fiber tract mapping from diffusion tensor MRI (DT-MRI) implemented on graphics hardware. From the simulated fibers we compute a connectivity map that gives an indication of the probability that two points in the dataset are connected by a neuronal fiber path. A Bayesian formulation of the fiber model is given and it is(More)
OBJECTIVES The purpose of this study was to compare a novel compressed sensing (CS)-based single-breath-hold multislice magnetic resonance cine technique with the standard multi-breath-hold technique for the assessment of left ventricular (LV) volumes and function. BACKGROUND Cardiac magnetic resonance is generally accepted as the gold standard for LV(More)
One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a(More)
There is increased use of medical imaging techniques that produce four dimensional (4D) datasets such as fMRI and 3D dynamic echocardiograms. These datasets consume even larger amounts of resources for transmission or storage compared to the traditional 2D data sets. In this paper, we extend the zero tree algorithms, EZW (embedded zero tree coding of(More)
Many medical imaging techniques available today generate 4D data sets. One such technique is functional magnetic resonance imaging (fMRI) which aims to determine regions of the brain that are activated due to various cognitive and/or motor functions or sensory stimuli. These data sets often require substantial resources for storage and transmission and(More)
Compressed Sensing (CS) theory has gained attention recently as an alternative to the current paradigm of sampling followed by compression. Early CS recovery techniques operated under the implicit assumption that the transform coefficients in the sparsity domain are independently distributed. Recent works, however, demonstrated that exploiting the(More)
This paper presents a novel technique for image restoration based on nonlinear interpolative vector quantization (NLIVQ). The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. It is trained on image pairs consisting of an original image and its diffraction-limited counterpart. The discrete cosine(More)
PURPOSE To integrate, optimize, and evaluate a three-dimensional (3D) contrast-enhanced sparse MRA technique with iterative reconstruction on a standard clinical MR system. METHODS Data were acquired using a highly undersampled Cartesian spiral phyllotaxis sampling pattern and reconstructed directly on the MR system with an iterative SENSE technique.(More)
The widespread use of multi-detector CT scanners has been associated with a remarkable increase in the number of CT slices as well as a substantial decrease in the average thickness of individual slices. This increased number of thinner slices has created a marked increase in archival and network bandwidth requirements associated with storage and(More)
This study evaluated the compressibility of multislice CT (MSCT) datasets and its dependence on (1) slice thickness and (2) the use of three-dimensional (3D) vs. 2D JPEG2000 compression methods. Five thoracic CT datasets were obtained using a 16-detector MSCT scanner with a collimation of 0.75 mm (120 kVp, 90 mAs) and reconstructed at five slice thicknesses(More)