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Conference Paper: Partial Fourier MRI Reconstruction Using Convolutional Neural Networks
| Title | Partial Fourier MRI Reconstruction Using Convolutional Neural Networks |
|---|---|
| Authors | |
| Issue Date | 2020 |
| Publisher | International Society for Magnetic Resonance in Medicine (ISMRM) . |
| Citation | Proceedings of the 28th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Virtual Conference, 8-14 August 2020, paper no. 3627 How to Cite? |
| Abstract | Convolutional neural network (CNN) has emerged as a powerful tool for medical image reconstruction. In this study, we designed and implemented a CNN model for partial Fourier MRI reconstruction, and compared its performance with the existing projection onto convex sets (POCS) method. The results demonstrated that our proposed deep learning approach could effectively recovered the high frequency components and outperformed the POCS method especially when partial Fourier fraction is close to 50%. |
| Description | Digital Poster Session: Acquisition, Reconstruction & Analysis: ML: Image Reconstruction: Machine Learning for Image Reconstruction 3 - paper no. 3627 |
| Persistent Identifier | http://hdl.handle.net/10722/289870 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Cao, P | - |
| dc.contributor.author | Xiao, L | - |
| dc.contributor.author | Liu, Y | - |
| dc.contributor.author | Zhao, Y | - |
| dc.contributor.author | Feng, Y | - |
| dc.contributor.author | Leong, TL | - |
| dc.contributor.author | Wu, EX | - |
| dc.date.accessioned | 2020-10-22T08:18:39Z | - |
| dc.date.available | 2020-10-22T08:18:39Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.citation | Proceedings of the 28th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Virtual Conference, 8-14 August 2020, paper no. 3627 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/289870 | - |
| dc.description | Digital Poster Session: Acquisition, Reconstruction & Analysis: ML: Image Reconstruction: Machine Learning for Image Reconstruction 3 - paper no. 3627 | - |
| dc.description.abstract | Convolutional neural network (CNN) has emerged as a powerful tool for medical image reconstruction. In this study, we designed and implemented a CNN model for partial Fourier MRI reconstruction, and compared its performance with the existing projection onto convex sets (POCS) method. The results demonstrated that our proposed deep learning approach could effectively recovered the high frequency components and outperformed the POCS method especially when partial Fourier fraction is close to 50%. | - |
| dc.language | eng | - |
| dc.publisher | International Society for Magnetic Resonance in Medicine (ISMRM) . | - |
| dc.relation.ispartof | Proceedings of International Society of Magnetic Resonance in Medicine (ISMRM) Virtual Conference & Exhibition, 2020 | - |
| dc.title | Partial Fourier MRI Reconstruction Using Convolutional Neural Networks | - |
| dc.type | Conference_Paper | - |
| dc.identifier.email | Leong, TL: tlleong@hku.hk | - |
| dc.identifier.email | Wu, EX: ewu@eee.hku.hk | - |
| dc.identifier.authority | Leong, TL=rp02483 | - |
| dc.identifier.authority | Wu, EX=rp00193 | - |
| dc.identifier.hkuros | 316617 | - |
| dc.identifier.spage | 3627 | - |
| dc.identifier.epage | 3627 | - |