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Conference Paper: Simultaneous denoising of multi-contrast MR images using a novel weighted nuclear norm minimization approach
Title | Simultaneous denoising of multi-contrast MR images using a novel weighted nuclear norm minimization approach |
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Authors | |
Issue Date | 2019 |
Publisher | International Society for Magnetic Resonance in Medicine. |
Citation | The 27th Annual Meeting & Exhibition of International Society for Magnetic Resonance in Medicine (ISMRM), Montreal, Canada, 11-16 May 2019, abstract no. p0669 How to Cite? |
Abstract | A typical clinical MRI scanning session produces image sets with same geometries but different contrasts. These multi-contrast images often share strong structural similarities or correlations despite their contrast differences. Most existing MRI denoising methods deal with single-contrast images independently, and fail to explore and utilize such correlations across contrasts. In this study, we present a simultaneous denoising method for multi-contrast images based on low rank multi-contrast patch matrix completion. This denoising method exploits the structural similarities across contrasts, and outperforms the traditional method. Further, it does not compromise the image fidelity in absence of any structural similarities across contrasts. |
Description | Power Pitch Poster Session - Machine Learning Unleashed 2: Acquisition, Reconstruction & Analysis - Abstract #0669 |
Persistent Identifier | http://hdl.handle.net/10722/275277 |
DC Field | Value | Language |
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dc.contributor.author | Zhao, Y | - |
dc.contributor.author | Liu, Y | - |
dc.contributor.author | Mak, HKF | - |
dc.contributor.author | Wu, EX | - |
dc.date.accessioned | 2019-09-10T02:39:16Z | - |
dc.date.available | 2019-09-10T02:39:16Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | The 27th Annual Meeting & Exhibition of International Society for Magnetic Resonance in Medicine (ISMRM), Montreal, Canada, 11-16 May 2019, abstract no. p0669 | - |
dc.identifier.uri | http://hdl.handle.net/10722/275277 | - |
dc.description | Power Pitch Poster Session - Machine Learning Unleashed 2: Acquisition, Reconstruction & Analysis - Abstract #0669 | - |
dc.description.abstract | A typical clinical MRI scanning session produces image sets with same geometries but different contrasts. These multi-contrast images often share strong structural similarities or correlations despite their contrast differences. Most existing MRI denoising methods deal with single-contrast images independently, and fail to explore and utilize such correlations across contrasts. In this study, we present a simultaneous denoising method for multi-contrast images based on low rank multi-contrast patch matrix completion. This denoising method exploits the structural similarities across contrasts, and outperforms the traditional method. Further, it does not compromise the image fidelity in absence of any structural similarities across contrasts. | - |
dc.language | eng | - |
dc.publisher | International Society for Magnetic Resonance in Medicine. | - |
dc.relation.ispartof | ISMRM (International Society for Magnetic Resonance in Medicine) 27th Annual Meeting, 2019 | - |
dc.title | Simultaneous denoising of multi-contrast MR images using a novel weighted nuclear norm minimization approach | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Liu, Y: loyalliu@hku.hk | - |
dc.identifier.email | Mak, HKF: makkf@hku.hk | - |
dc.identifier.email | Wu, EX: ewu@eee.hku.hk | - |
dc.identifier.authority | Mak, HKF=rp00533 | - |
dc.identifier.authority | Wu, EX=rp00193 | - |
dc.identifier.hkuros | 304421 | - |
dc.identifier.hkuros | 307702 | - |
dc.identifier.spage | p0669 | - |
dc.identifier.epage | p0669 | - |