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Conference Paper: Multi-Contrast MRI Reconstruction from Single-Channel Uniformly Undersampled Data via Deep Learning

TitleMulti-Contrast MRI Reconstruction from Single-Channel Uniformly Undersampled Data via Deep Learning
Authors
Man, CXiao, LLiu, YLau, VYi, ZLeong, TLWu, EX
Issue Date2021
PublisherInternationala Society of Magnetic Resonance Imaging (ISMRM) .
Citation
Proceedings of the 29th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Virtual Conference, Vancouver, BC, Canada, 15-20 May 2021, paper no. 2431 How to Cite?
AbstractThis study presents a deep learning based reconstruction for multi-contrast MR data with orthogonal undersampling directions across different contrasts. It enables exploiting the rich structural similarities from multiple contrasts as well as the incoherency arose from complementary sampling. The results show that the proposed method can achieve robust reconstruction for single-channel multi-contrast MR data at R=4.
DescriptionDigital Posters Session D-118: Machine Learning for Image Analysis - Machine Learning: Multimodal & Multireader Insights - no.2431
Persistent Identifierhttp://hdl.handle.net/10722/304353

 

DC FieldValueLanguage
dc.contributor.authorMan, C-
dc.contributor.authorXiao, L-
dc.contributor.authorLiu, Y-
dc.contributor.authorLau, V-
dc.contributor.authorYi, Z-
dc.contributor.authorLeong, TL-
dc.contributor.authorWu, EX-
dc.date.accessioned2021-09-23T08:58:52Z-
dc.date.available2021-09-23T08:58:52Z-
dc.date.issued2021-
dc.identifier.citationProceedings of the 29th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Virtual Conference, Vancouver, BC, Canada, 15-20 May 2021, paper no. 2431-
dc.identifier.urihttp://hdl.handle.net/10722/304353-
dc.descriptionDigital Posters Session D-118: Machine Learning for Image Analysis - Machine Learning: Multimodal & Multireader Insights - no.2431-
dc.description.abstractThis study presents a deep learning based reconstruction for multi-contrast MR data with orthogonal undersampling directions across different contrasts. It enables exploiting the rich structural similarities from multiple contrasts as well as the incoherency arose from complementary sampling. The results show that the proposed method can achieve robust reconstruction for single-channel multi-contrast MR data at R=4.-
dc.languageeng-
dc.publisherInternationala Society of Magnetic Resonance Imaging (ISMRM) .-
dc.relation.ispartofISMRM (International Society of Magnetic Resonance Imaging) Virtual Conference & Exhibition, 2021-
dc.titleMulti-Contrast MRI Reconstruction from Single-Channel Uniformly Undersampled Data via Deep Learning-
dc.typeConference_Paper-
dc.identifier.emailLeong, TL: tlleong@hku.hk-
dc.identifier.emailWu, EX: ewu@eee.hku.hk-
dc.identifier.authorityLeong, TL=rp02483-
dc.identifier.authorityWu, EX=rp00193-
dc.identifier.hkuros325464-
dc.identifier.spage2431-
dc.identifier.epage2431-

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