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Conference Paper: Direct diffusion tensor estimation using joint sparsity constraint without image reconstruction
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TitleDirect diffusion tensor estimation using joint sparsity constraint without image reconstruction
 
AuthorsZhu, Y
Wu, Y
Wu, EX
Ying, L
Liang, D
 
Issue Date2012
 
PublisherInternational Society of Magnetic Resonance in Medicine.
 
CitationThe 20th Annual Meeting & Exihibition of the International Society of Magnetic Resonance in Medicine (ISMRM 2012), Melbourne, Australia, 5-11 May 2012. In Proceedings of the 20th ISMRM, 2012, no. 0009 [How to Cite?]
 
AbstractThe joint sparsity constraint is integrated into the model-based method to improve the accuracy of direct diffusion tensor estimation from highly undersampled k-space data. The method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion weighted images in solving the nonlinear equation of tensors. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.
 
DescriptionTheme: Adapting MR in a Changing World
Oral Presentation - Session 01: Compressed Sensing - Novel Applications: no. 0009
 
DC FieldValue
dc.contributor.authorZhu, Y
 
dc.contributor.authorWu, Y
 
dc.contributor.authorWu, EX
 
dc.contributor.authorYing, L
 
dc.contributor.authorLiang, D
 
dc.date.accessioned2012-09-20T08:16:04Z
 
dc.date.available2012-09-20T08:16:04Z
 
dc.date.issued2012
 
dc.description.abstractThe joint sparsity constraint is integrated into the model-based method to improve the accuracy of direct diffusion tensor estimation from highly undersampled k-space data. The method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion weighted images in solving the nonlinear equation of tensors. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.
 
dc.description.naturelink_to_OA_fulltext
 
dc.descriptionTheme: Adapting MR in a Changing World
 
dc.descriptionOral Presentation - Session 01: Compressed Sensing - Novel Applications: no. 0009
 
dc.description.otherThe 20th Annual Meeting & Exihibition of the International Society of Magnetic Resonance in Medicine (ISMRM 2012), Melbourne, Australia, 5-11 May 2012. In Proceedings of the 20th ISMRM, 2012, no. 0009
 
dc.identifier.citationThe 20th Annual Meeting & Exihibition of the International Society of Magnetic Resonance in Medicine (ISMRM 2012), Melbourne, Australia, 5-11 May 2012. In Proceedings of the 20th ISMRM, 2012, no. 0009 [How to Cite?]
 
dc.identifier.hkuros207268
 
dc.identifier.urihttp://hdl.handle.net/10722/165179
 
dc.languageeng
 
dc.publisherInternational Society of Magnetic Resonance in Medicine.
 
dc.publisher.placeAustralia
 
dc.relation.ispartofProceedings of the 20th Annual Meeting of the International Society of Magnetic Resonance in Medicine, ISMRM 2012
 
dc.titleDirect diffusion tensor estimation using joint sparsity constraint without image reconstruction
 
dc.typeConference_Paper
 
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