Sciweavers

Share
ISBI
2011
IEEE

K-SVD for HARDI denoising

11 years 1 months ago
K-SVD for HARDI denoising
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.
Vishal Patel, Yonggang Shi, Paul M. Thompson, Arth
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ISBI
Authors Vishal Patel, Yonggang Shi, Paul M. Thompson, Arthur W. Toga
Comments (0)
books