Stephen F. Cauley1, Obaidah A. Abuhashem2, Berkin Bilgic3, Itthi Chatnuntawech3, Julien Cohen-Adad4, Kawin Setsompop5, Elfar Adalsteinsson2, 5, Lawrence L. Wald5, 6
1A.A. Martinos Center for Biomedical Imaging, Dept. of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; 2Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States; 3Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States; 4Department of Electrical Engineering, Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada; 5A.A. Martinos Center for Biomedical Imaging, Dept. of Radiology, MGH, Charlestown, MA, United States; 6Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA, United States
The substantial signal attenuation in DI images for large b-values can affect accurate calculation of orientation distribution functions (odf) and fiber tracks. In addition, the low signal-to-noise (SNR) observed at large b-values hinders the performance of popular denoising methods like the LMMSE estimator and the NLM filter. In this work we demonstrate the benefits of basis smoothing within a low-rank DWI estimation framework. Our method significantly reduces the dependencies on noisy basis vectors while preserving root-mean-square error (RMSE) relative to low-noise data (computed by averaging multiple acquisitions).