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Computational and Mathematical Methods in Medicine
Volume 2018, Article ID 7680164, 12 pages
Research Article

A PSO-Powell Hybrid Method to Extract Fiber Orientations from ODF

1School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
2Department of Systems Medicine & Bioengineering, Houston Methodist Hospital, Houston, TX, USA
3Department of Biomedical Engineering, University of Houston, Houston, TX, USA

Correspondence should be addressed to Xiaohui Yu; gro.tsidohtemnotsuoh@2uyx

Received 4 August 2017; Revised 20 December 2017; Accepted 26 December 2017; Published 21 January 2018

Academic Editor: Chuangyin Dang

Copyright © 2018 Zhanxiong Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


High angular resolution diffusion imaging (HARDI) has opened up new perspectives for the delineation of crossing and branching fiber pathways by orientation distribution function (ODF). The fiber orientations contained in an imaging voxel are the key factor in tractography. To extract real fiber orientations from ODF, a hybrid method is proposed for computing the principal directions of ODF by combining the variation of Particle Swarm Optimization (PSO) algorithm with the modified Powell algorithm. This method is comprised of the global searching ability of PSO and the powerful local optimizing of Powell search. This combination can guarantee finding all the diffusion directions without applying sliding windows and improve the accuracy and efficiency. The proposed approach was evaluated on simulated crossing-fiber datasets, Tractometer, and in vivo datasets. The results show that this method could correctly identify fiber directions under a range of noise levels. This method was compared with the state-of-the-art methods, such as modified Powell, ball-stick model, and diffusion decomposition, showing that it outperformed them. As to the multimodal voxels where different fiber populations exist, the proposed approach allows us to improve the estimation accuracy of fiber orientations from ODF. It can play a significant role in the nerve fiber tracking.