Incorporating independent component analysis to Q-ball imaging for diffusion orientation distribution reconstruction

M. Jing*, T. M. McGinnity, S. Coleman, H. Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

2 Citations (Scopus)

Abstract

In this paper, we investigate the incorporation of independent component analysis (ICA) with Q-ball imaging (QBI) to extract information on the diffusion orientation distribution function (ODF) from an inner voxel. In our approach, the ICA algorithm is applied to a mixture of ODFs which are constructed based on the analytical QBI solution. The numerical simulation results demonstrate that the proposed ICA framework can not only successfully separate the diffusion ODF from the noisy diffusion data, but also achieves better performance compared with a QBI solution when the data has a low signal to noise ratio (SNR).

Original languageEnglish
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages2706-2709
Number of pages4
DOIs
Publication statusPublished - 1 Nov 2010
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: 31 Aug 20104 Sept 2010

Publication series

Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conference

Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Country/TerritoryArgentina
CityBuenos Aires
Period31/08/104/09/10

Fingerprint

Dive into the research topics of 'Incorporating independent component analysis to Q-ball imaging for diffusion orientation distribution reconstruction'. Together they form a unique fingerprint.

Cite this