J Math Imaging Vis DOI 10.1007/s10851-008-0071-8 High Angular Resolution Diffusion MRI Segmentation Using Region-Based Statistical Surface Evolution

Abstract In this article we develop a new method to seg-ment high angular resolution diffusion imaging (HARDI) data. We first estimate the orientation distribution function (ODF) using a fast and robust spherical harmonic (SH) method. Then, we use a region-based statistical surface evo-lution on this image of ODFs to efficiently find coherent white matter fiber bundles. We show that our method is ap-propriate to propagate through regions of fiber crossings and we show that our results outperform state-of-the-art diffu-sion tensor (DT) imaging segmentation methods, inherently limited by the DT model. Results obtained on synthetic data, on a biological phantom, on real datasets and on all 13 sub-jects of a public NMR database show that our method is reproducible, automatic and brings a strong added value to diffusion MRI segmentation. Keywords Diffusion tensor imaging (DTI) · High angular resolution diffusion imaging (HARDI) · Q-ball imaging (QBI) · Orientation distribution function (ODF) · Region-based segmentation · Level set framework