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A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Zhang, Huaizhong, McGinnity, TM, Coleman, SA and Jing, Min (2010) A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique. In: International Conference on Medical Biometrics. Springer. 10 pp. [Conference contribution]

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DOI: 10.1007/978-3-642-13923-9_44

Abstract

Based on the spherical harmonic decomposition of HARDI data, we propose a new criterion for characterizing the diffusion anisotropy in a voxel directly from the SH coefficients. Essentially, by considering the Rician noise in diffusion data, we modify the Rissanen’s criterion for fitting the diffusion situation in a voxel. In addition, the minimum description length (MDL) criterion has been employed for interpreting information from both the SH coefficients and the data. The criterion obtained can make use of the diffusion information so as to efficiently separate the different diffusion distributions. Various synthetic datasets have been used for verifying our method. The experimental results show the performance of the proposed criterion is accurate

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
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:15360
Deposited By:Dr Sonya Coleman
Deposited On:01 Sep 2010 11:08
Last Modified:01 Sep 2010 11:08

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