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

Huaizhong Zhang, TM McGinnity, SA Coleman, Min Jing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages413-422
Number of pages10
DOIs
Publication statusPublished - 9 Jun 2010
EventInternational Conference on Medical Biometrics -
Duration: 9 Jun 2010 → …

Conference

ConferenceInternational Conference on Medical Biometrics
Period9/06/10 → …

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Anisotropy
Decomposition

Cite this

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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",
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A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique. / Zhang, Huaizhong; McGinnity, TM; Coleman, SA; Jing, Min.

Unknown Host Publication. 2010. p. 413-422.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Coleman, SA

AU - Jing, Min

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N2 - 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

AB - 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

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