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K-SVD for HARDI denoising

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4 Author(s)
Vishal Patel ; Laboratory of Neuro Imaging, University of California, Los Angeles, USA ; Yonggang Shi ; Paul M. Thompson ; Arthur W. Toga

Noise is an important concern in high-angular resolution diffusion imaging studies because it can lead to errors in downstream analyses of white matter structure. To address this issue, we investigate a new approach for denoising diffusion-weighted data sets based on the K-SVD algorithm. We analyze its characteristics using both simulated and biological data and compare its performance with existing methods. Our results show that K-SVD provides robust and effective noise reduction and is practical for use in high-volume applications.

Published in:

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Date of Conference:

March 30 2011-April 2 2011