On Monday May 7th, I present the results I obtained during one project I took on during my second semester of my Masters program. The topic is on MR velocity imaging and regularization of images. Basically the goal is to acquire noisy images while sampling less data. The reasoning behind this is that it is less expensive to sample less data that is noisy than to acquire complete noiseless data which would require more time and higher costs. Given a sampling strategy, the algorithm reconstructs the image in Matlab and attempts to filter out the noise from this partial data. I also investigated several sampling strategies and the results were quite interesting. Hopefully a paper can be published from this, but it still requires that the model be extended by another dimension - time for example. The paper and slides can be obtained from:
http://www.cas.mcmaster.ca/~elshawn/
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