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Conference Paper: Accelerated Magnetic Resonance Fingerprinting Reconstruction using Majorization-Minimization
Title | Accelerated Magnetic Resonance Fingerprinting Reconstruction using Majorization-Minimization |
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Authors | |
Issue Date | 2017 |
Publisher | International Society for Magnetic Resonance in Medicine. |
Citation | The 25th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 22-27 April 2017. In Conference Proceedings, 2017, abstract no. 1356 How to Cite? |
Abstract | Magnetic resonance fingerprinting (MRF) is a novel and efficient method for the estimation of MR parameters, such as off-resonance (DB0), proton density (PD), T1 and T2. Because of the highly undersampled readout that is conventionally used, large number of dynamics (e.g. <1000) are often acquired for maintaining the fidelity of MR parameter estimations (a.k.a. dictionary matching). In this study, we propose a new algorithm, MRF reconstruction using majorization-minimization (mmMRF), such that fidelity of dictionary matching can remain similar even when significantly less number of dynamics are available. |
Persistent Identifier | http://hdl.handle.net/10722/240986 |
DC Field | Value | Language |
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dc.contributor.author | Li, Y | - |
dc.contributor.author | Wang, S | - |
dc.contributor.author | Hui, SK | - |
dc.contributor.author | Cui, D | - |
dc.contributor.author | Chang, HCC | - |
dc.contributor.author | Wu, YC | - |
dc.date.accessioned | 2017-05-22T09:20:37Z | - |
dc.date.available | 2017-05-22T09:20:37Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | The 25th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 22-27 April 2017. In Conference Proceedings, 2017, abstract no. 1356 | - |
dc.identifier.uri | http://hdl.handle.net/10722/240986 | - |
dc.description.abstract | Magnetic resonance fingerprinting (MRF) is a novel and efficient method for the estimation of MR parameters, such as off-resonance (DB0), proton density (PD), T1 and T2. Because of the highly undersampled readout that is conventionally used, large number of dynamics (e.g. <1000) are often acquired for maintaining the fidelity of MR parameter estimations (a.k.a. dictionary matching). In this study, we propose a new algorithm, MRF reconstruction using majorization-minimization (mmMRF), such that fidelity of dictionary matching can remain similar even when significantly less number of dynamics are available. | - |
dc.language | eng | - |
dc.publisher | International Society for Magnetic Resonance in Medicine. | - |
dc.relation.ispartof | ISMRM 2017 Annual Meeting & Exhibition Proceedings | - |
dc.title | Accelerated Magnetic Resonance Fingerprinting Reconstruction using Majorization-Minimization | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Hui, SK: edshui@hku.hk | - |
dc.identifier.email | Chang, HCC: hcchang@hku.hk | - |
dc.identifier.email | Wu, YC: ycwu@eee.hku.hk | - |
dc.identifier.authority | Hui, SK=rp01832 | - |
dc.identifier.authority | Chang, HCC=rp02024 | - |
dc.identifier.authority | Wu, YC=rp00195 | - |
dc.identifier.hkuros | 272202 | - |
dc.publisher.place | United States | - |