EconPapers    
Economics at your fingertips  
 

Regularization of DT‐MRI Using 3D Median Filtering Methods

Soondong Kwon, Dongyoun Kim, Bongsoo Han and Kiwoon Kwon

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

Abstract: DT‐MRI (diffusion tensor magnetic resonance imaging) tractography is a method to determine the architecture of axonal fibers in the central nervous system by computing the direction of the principal eigenvectors obtained from tensor matrix, which is different from the conventional isotropic MRI. Tractography based on DT‐MRI is known to need many computations and is highly sensitive to noise. Hence, adequate regularization methods, such as image processing techniques, are in demand. Among many regularization methods we are interested in the median filtering method. In this paper, we extended two‐dimensional median filters already developed to three‐dimensional median filters. We compared four median filtering methods which are two‐dimensional simple median method (SM2D), two‐dimensional successive Fermat method (SF2D), three‐dimensional simple median method (SM3D), and three‐dimensional successive Fermat method (SF3D). Three kinds of synthetic data with different altitude angles from axial slices and one kind of human data from MR scanner are considered for numerical implementation by the four filtering methods.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2014/285367

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:285367

Access Statistics for this article

More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-22
Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:285367