Fast T2 relaxation data analysis with stimulated echo correction and non-local spatial regularisation

This tool is developed to offer a fast algorithm for computing myelin maps from multiecho T2 relaxation data using parallel computation with multicore CPUs and graphics processing units (GPUs). The tool also provides non-local spatial regularization to produce more accurate and reliable myelin maps for noisy T2 relaxation data.

The details of the method are given the following papers:

Yoo, Youngjin et al., "Fast computation of myelin maps from MRI T2 relaxation data using multicore CPU and graphics card parallelization." Journal of Magnetic Resonance Imaging (2014).

Yoo, Youngjin, and Roger Tam. "Non-local spatial regularization of MRI T2 relaxation images for myelin water quantification." In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013, pp. 614-621. Springer Berlin Heidelberg, 2013.

The JMRI paper stated that we intented to contribute to Gadgetron, but we found that NITRC seems to be a better fit so we have decided to share our code through NITRC.

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