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Abstract #2243

High Spatial and Angular Resolution Diffusion Imaging Using Compressed Sensing

Merry Mani1, 2, Mathews Jacob3, Arnaud Guidon4, Chunlei Liu, Allen Song, Jianhui Zhong, 2

1Electrical and Computer Engineering, University of Rochester, Rochester, NY, United States; 2Rochester Center for Brain Imaging, Rochester, NY, United States; 3Electrical and Computer Engineering, University of Iowa; 4Biomedical Engineering, Duke University

Both high angular and high spatial resolution are highly desirable in diffusion imaging applications. However, the acquisition time gets prohibitively long as the resolution in both dimensions are increased. We propose a new acquisition strategy to simultaneously enhance the resolution in both dimensions of diffusion imaging in a reasonable scan time. We achieve this by under-sampling the combined k-q acquisition space of diffusion imaging and using a compressed sensing strategy for reconstruction. Results show that at least 6 fold acceleration in scan time is possible, making it feasible to achieve 1mm in-plane resolution and high angular resolution in around 8 minutes.