Accelerated diffusion operators for enhancing DW-MRI

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

the intra-voxel diffusion pattern compared to its simpler predecessor diffusion tensor imaging (DTI). However, HARDI in general produces very noisy diffusion patterns due to the low SNR from the scanners at high b-values. Furthermore, it still exhibits limitations in areas where the diffusion pattern is asymmetrical (bifurcations, splaying fibers, etc.). To overcome these limitations, enhancement and denoising of the data based on context information is a crucial step. In order to achieve it, convolutions are performed in the coupled spatial and angular domain. Therefore the kernels applied become also HARDI data. However, these approaches have high computational complexity of an already complex HARDI data processing. In this work, we present an accelerated framework for HARDI data regularizaton and enhancement. The convolution operators are optimized by: pre-calculating the kernels, analysing kernels shape and utilizing look-up-tables. We provide an increase of speed, compared to previous brute force approaches of simpler kernels. These methods can be used as a preprocessing for tractography and lead to new ways for investigation of brain white matter.
Original languageEnglish
Title of host publicationEurographics Workshop on Visual Computing for Biology and Medicine
PublisherThe Eurographics Association
Number of pages8
ISBN (Electronic)978-3-905674-28-6
DOIs
Publication statusPublished - 2010
Event2nd Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM 2010) - Leipzig, Germany
Duration: 1 Jul 20102 Jul 2010

Conference

Conference2nd Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM 2010)
CountryGermany
CityLeipzig
Period1/07/102/07/10

Fingerprint Dive into the research topics of 'Accelerated diffusion operators for enhancing DW-MRI'. Together they form a unique fingerprint.

Cite this