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Article: The measure of diffusion skewness and kurtosis in magnetic resonance imaging

TitleThe measure of diffusion skewness and kurtosis in magnetic resonance imaging
Authors
KeywordsEigenvalues
Generalized Diffusion Tensor Imaging
Kurtosis
Signal Processing
Skewness
Issue Date2010
PublisherYokohama Publishers. The Journal's web site is located at http://www.ybook.co.jp/pjo.html
Citation
Pacific Journal Of Optimization, 2010, v. 6 n. 2, p. 391-404 How to Cite?
AbstractThe diffusion tensor imaging (DTI) model is an important magnetic resonance imaging (MRI) model in biomedical engineering. It assumes that the water molecule displacement distribution is a Gaussian function. However, water movement in biological tissue is often non-Gaussian and this non-Gaussian behavior may contain useful biological and clinical information. In order to overcome this drawback, a new MRI model, the generalized diffusion tensor imaging (GDTI) model, was presented in [8]. In the GDTI model, even order tensors reflect the magnitude of the signal, while odd order tensors reflect the phase of the signal. In this paper, we propose to use the apparent skewness coefficient (ASC) value to measure the phase of non-Gaussian signals. We prove that the ASC values are invariant under rotations of co-ordinate systems. We discuss some further properties of the diffusion kurtosis tensor and present some preliminary numerical experiments for calculating the ASC values. © 2010 Yokohama Publishers.
Persistent Identifierhttp://hdl.handle.net/10722/155602
ISSN
2015 Impact Factor: 0.307
2015 SCImago Journal Rankings: 0.549
References

 

DC FieldValueLanguage
dc.contributor.authorZhang, Xen_US
dc.contributor.authorLing, Cen_US
dc.contributor.authorQi, Len_US
dc.contributor.authorWu, EXen_US
dc.date.accessioned2012-08-08T08:34:19Z-
dc.date.available2012-08-08T08:34:19Z-
dc.date.issued2010en_US
dc.identifier.citationPacific Journal Of Optimization, 2010, v. 6 n. 2, p. 391-404en_US
dc.identifier.issn1348-9151en_US
dc.identifier.urihttp://hdl.handle.net/10722/155602-
dc.description.abstractThe diffusion tensor imaging (DTI) model is an important magnetic resonance imaging (MRI) model in biomedical engineering. It assumes that the water molecule displacement distribution is a Gaussian function. However, water movement in biological tissue is often non-Gaussian and this non-Gaussian behavior may contain useful biological and clinical information. In order to overcome this drawback, a new MRI model, the generalized diffusion tensor imaging (GDTI) model, was presented in [8]. In the GDTI model, even order tensors reflect the magnitude of the signal, while odd order tensors reflect the phase of the signal. In this paper, we propose to use the apparent skewness coefficient (ASC) value to measure the phase of non-Gaussian signals. We prove that the ASC values are invariant under rotations of co-ordinate systems. We discuss some further properties of the diffusion kurtosis tensor and present some preliminary numerical experiments for calculating the ASC values. © 2010 Yokohama Publishers.en_US
dc.languageengen_US
dc.publisherYokohama Publishers. The Journal's web site is located at http://www.ybook.co.jp/pjo.htmlen_US
dc.relation.ispartofPacific Journal of Optimizationen_US
dc.subjectEigenvaluesen_US
dc.subjectGeneralized Diffusion Tensor Imagingen_US
dc.subjectKurtosisen_US
dc.subjectSignal Processingen_US
dc.subjectSkewnessen_US
dc.titleThe measure of diffusion skewness and kurtosis in magnetic resonance imagingen_US
dc.typeArticleen_US
dc.identifier.emailWu, EX:ewu1@hkucc.hku.hken_US
dc.identifier.authorityWu, EX=rp00193en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-79951499925en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79951499925&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume6en_US
dc.identifier.issue2en_US
dc.identifier.spage391en_US
dc.identifier.epage404en_US
dc.publisher.placeJapanen_US
dc.identifier.scopusauthoridZhang, X=8834497200en_US
dc.identifier.scopusauthoridLing, C=7202027903en_US
dc.identifier.scopusauthoridQi, L=7202149952en_US
dc.identifier.scopusauthoridWu, EX=7202128034en_US

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