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.