Bennett Allan Landman1,2, Hanlin Wan2,3, John A. Bogovic3, Peter C. M. van Zijl4,5, Pierre-Louis Bazin6, Jerry L. Prince, 23
1Electrical Engineering, Vanderbilt University, Nashville, TN, United States; 2Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States; 3Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States; 4F.M. Kirby Center, Kennedy Krieger Institute, Baltimore, MD, United States; 5Biomedical Engineering, Johns Hopkins University, Nashville, TN, United States; 6Radiology, Johns Hopkins University, Baltimore, MD, United States
Compressed sensing is a promising technique to estimate intra-voxel structure with traditional DTI data and avoid many of the practical constraints (e.g., long scan times, low signal-to-noise ratio) that plague more detailed, high b-value studies. However, computational complexity is a major limitation of compressed sensing techniques as currently proposed. We demonstrate a novel technique for accelerated compressed sensing of diffusion-inferred intra-voxel structure utilizing adaptive refinement of a multi-resolution basis set. Our approach achieves a tenfold reduction in computational complexity and enables more practical consideration of intra-voxel orientations in time-sensitive settings, routine data analysis, or in large studies.