Conference Paper: Direct diffusion tensor estimation using joint sparsity constraint without image reconstruction
| Title | Direct diffusion tensor estimation using joint sparsity constraint without image reconstruction |
|---|---|
| Authors | Zhu, Y Wu, Y Wu, EX Ying, L Liang, D |
| Issue Date | 2012 |
| Publisher | International Society of Magnetic Resonance in Medicine. |
| Citation | The 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?] |
| Abstract | The 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. |
| Description | Theme: Adapting MR in a Changing World Oral Presentation - Session 01: Compressed Sensing - Novel Applications: no. 0009 |
| dc.contributor.author | Zhu, Y |
|---|---|
| dc.contributor.author | Wu, Y |
| dc.contributor.author | Wu, EX |
| dc.contributor.author | Ying, L |
| dc.contributor.author | Liang, D |
| dc.date.accessioned | 2012-09-20T08:16:04Z |
| dc.date.available | 2012-09-20T08:16:04Z |
| dc.date.issued | 2012 |
| dc.description.abstract | The 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.nature | link_to_OA_fulltext |
| dc.description | Theme: Adapting MR in a Changing World |
| dc.description | Oral Presentation - Session 01: Compressed Sensing - Novel Applications: no. 0009 |
| dc.description.other | The 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.citation | The 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.hkuros | 207268 |
| dc.identifier.uri | http://hdl.handle.net/10722/165179 |
| dc.language | eng |
| dc.publisher | International Society of Magnetic Resonance in Medicine. |
| dc.publisher.place | Australia |
| dc.relation.ispartof | Proceedings of the 20th Annual Meeting of the International Society of Magnetic Resonance in Medicine, ISMRM 2012 |
| dc.title | Direct diffusion tensor estimation using joint sparsity constraint without image reconstruction |
| dc.type | Conference_Paper |