Abstract #1686

Analytical Q-Ball Imaging with Optimal λ-Regularization

Maxime Descoteaux¹, Cheng Guan Koay², Peter J. Basser², Rachid Deriche³

¹Computer Science, Universit de Sherbrooke, Sherbrooke, Qubec, Canada; ²National Institute of Child Health and Human Development, Bethesda, MD, United States; ³INRIA Sophia Antipolis - Mditerrane, Sophia Antipolis, France

We present analytical q-ball imaging with optimal Generalized Cross Validation (GCV)-based regularization. The method is the optimal extension of the standard analytical q-ball imaging, normally implemented using a fixed regularization λ = 0.006. QBI with optimal λ shows a distinct advantage in generalized fractional anisotropy (GFA) computation when the underlying structure is complex and in single fiber parts of real data.