Ulster University Logo

Estimation of the Underlying Fiber Orientation Using Spherical k-means Method from the Diffusion ODF in HARDI Data

Zhang, Huaizhong, McGinnity, TM, Coleman, SA and Jing, Min (2011) Estimation of the Underlying Fiber Orientation Using Spherical k-means Method from the Diffusion ODF in HARDI Data. In: Irish Conference on Artificial Intelligence and Cognitive Science, Londonderry. ISRC Technical report series. 10 pp. [Conference contribution]

Full text not available from this repository.

Abstract

This paper presents a new approach for detecting the underlying fiber directions in a voxel. The main idea is to use the principal direction (centroid of orientation class) of an orientation population instead of the classical maximal direction of diffusion orientation density function (ODF) for fiber orientation. Firstly, diffusion orientations from the ODF of raw data are classified in accordance with the expected fiber populations. The centroids of diffusion orientations are then determined using the spherical k-means method so as to estimate fiber orientations. The proposed method is based on the reconstruction of diffusion ODF using spherical harmonic (SH) decomposition and the characterization of diffusion anisotropy in a voxel. It can approximate fiber orientations accurately and avoid the spurious detection of fiber orientation which is often observed with traditional methods. By using a variety of synthetic, phantom and real datasets, the experimental results demonstrate the effectiveness of the proposed method.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:19898
Deposited By: Dr Sonya Coleman
Deposited On:26 Sep 2011 08:58
Last Modified:26 Sep 2011 08:58

Repository Staff Only: item control page