Abstract #0653

Robust Myelin Water Quantification Using Spatially Regularized Nonnegative Least Square Algorithm

Dosik Hwang¹, Yiping P. Du²

¹Electrical and Electronic Engineering, Yonsei University, Seoul, Korea; ²Psychiatry, University of Colorado Denver, Denver, CO, USA

A spatially regularized nonnegative least square algorithm was developed for robust myelin water quantification in the brain. The regularization of the conventional nonnegative least square (NNLS) algorithm has been expanded into the spatial domain in addition to the spectral domain. A substantial decrease in the myelin water fraction (MWF) variability was observed in both simulation results and the analysis of experimental data. In contrast to other filtering approaches that reduced the noise with a penalty of reduced spatial resolution, this new algorithm effectively preserved details of myelin distribution with substantial noise reduction. The visibility of small focal lesions was greatly improved.