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Conference Paper: Accelerated Magnetic Resonance Fingerprinting Using Convolutional Neural Network
| Title | Accelerated Magnetic Resonance Fingerprinting Using Convolutional Neural Network |
|---|---|
| Authors | |
| Issue Date | 2018 |
| Publisher | International Society for Magnetic Resonance in Medicine. |
| Citation | Joint International Society for Magnetic Resonance in Medicine & The European Society for Magnetic Resonance in Medicine and Biology (ISMRM-ESMRMB) Annual Meeting, Paris, France, 16-21 June 2018, abstract no. 4269 How to Cite? |
| Abstract | The purpose of this work is to accelerate the acquisition of Magnetic Resonance Fingerprinting (MRF) using Convolutional Neural Network (CNN). Compared with traditional MRF reconstruction using 1000 time points, our CNN model shows better reconstruction fidelity in T2 and similar reconstruction fidelity in T1 using 300 time points. Our study suggests that CNN-based method may be an effective tool in the acceleration of MRF reconstruction. |
| Description | E-Poster Session - Acquisition, Reconstruction & Analysis: MR Fingerprinting - no. 4269 |
| Persistent Identifier | http://hdl.handle.net/10722/259678 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Liao, Y | - |
| dc.contributor.author | Zhang, Q | - |
| dc.contributor.author | Cui, D | - |
| dc.contributor.author | Hui, SK | - |
| dc.contributor.author | Chen, H | - |
| dc.date.accessioned | 2018-09-03T04:12:00Z | - |
| dc.date.available | 2018-09-03T04:12:00Z | - |
| dc.date.issued | 2018 | - |
| dc.identifier.citation | Joint International Society for Magnetic Resonance in Medicine & The European Society for Magnetic Resonance in Medicine and Biology (ISMRM-ESMRMB) Annual Meeting, Paris, France, 16-21 June 2018, abstract no. 4269 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/259678 | - |
| dc.description | E-Poster Session - Acquisition, Reconstruction & Analysis: MR Fingerprinting - no. 4269 | - |
| dc.description.abstract | The purpose of this work is to accelerate the acquisition of Magnetic Resonance Fingerprinting (MRF) using Convolutional Neural Network (CNN). Compared with traditional MRF reconstruction using 1000 time points, our CNN model shows better reconstruction fidelity in T2 and similar reconstruction fidelity in T1 using 300 time points. Our study suggests that CNN-based method may be an effective tool in the acceleration of MRF reconstruction. | - |
| dc.language | eng | - |
| dc.publisher | International Society for Magnetic Resonance in Medicine. | - |
| dc.relation.ispartof | ISMRM-ESMRMB Annual Meeting 2018 | - |
| dc.title | Accelerated Magnetic Resonance Fingerprinting Using Convolutional Neural Network | - |
| dc.type | Conference_Paper | - |
| dc.identifier.email | Hui, SK: edshui@hku.hk | - |
| dc.identifier.authority | Hui, SK=rp01832 | - |
| dc.identifier.hkuros | 287949 | - |
| dc.identifier.spage | abstract no. 4269 | - |
| dc.identifier.epage | abstract no. 4269 | - |
| dc.publisher.place | United States | - |