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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.