Ajit Devaraj

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We present a Wiener filtering based algorithm for the elimination of motion artifacts present in Near Infrared (NIR) spectroscopy measurements. Until now, adaptive filtering was the only technique used in the noise cancellation in NIR studies. The results in this preliminary study revealed that the proposed method gives better estimates than the classical(More)
A novel center-out 3D trajectory for sampling magnetic resonance data is presented. The trajectory set is based on a single Fermat spiral waveform, which is substantially undersampled in the center of k-space. Multiple trajectories are combined in a "stacked cone" configuration to give very uniform sampling throughout a "hub," which is very efficient in(More)
Timing delays between data acquisition and gradient transmission result in image degradation. This is especially true in spiral MRI, where delays can alter data in a nonuniform manner, generating significant artifact in the reconstructed data. The many methods that exist to mitigate these delays or measure the k-space coordinates require long measurement(More)
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