Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging
ABSTRACT: Achieving sufficient spatial and temporal resolution for dynamic applications in cardiovascular magnetic resonance (CMR) imaging is a challenging task due to the inherently slow nature of CMR. In order to accelerate scans and allow improved resolution, much research over the past three dec...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Journal of Cardiovascular Magnetic Resonance |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1097664725000353 |
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| author | Andrew Phair René M. Botnar Claudia Prieto |
| author_facet | Andrew Phair René M. Botnar Claudia Prieto |
| author_sort | Andrew Phair |
| collection | DOAJ |
| description | ABSTRACT: Achieving sufficient spatial and temporal resolution for dynamic applications in cardiovascular magnetic resonance (CMR) imaging is a challenging task due to the inherently slow nature of CMR. In order to accelerate scans and allow improved resolution, much research over the past three decades has been aimed at developing innovative reconstruction methods that can yield high-quality images from reduced amounts of k-space data. In this review, we describe the evolution of these reconstruction techniques, with a particular focus on those advances that have shifted the dynamic reconstruction paradigm as it relates to CMR. This review discusses and explains the fundamental ideas behind the success of modern reconstruction algorithms, including parallel imaging, spatio-temporal redundancies, compressed sensing, low-rank methods and machine learning. |
| format | Article |
| id | doaj-art-fdce4aefbbcb4f8786770c5d3c0fc0f5 |
| institution | Kabale University |
| issn | 1097-6647 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Cardiovascular Magnetic Resonance |
| spelling | doaj-art-fdce4aefbbcb4f8786770c5d3c0fc0f52025-08-20T03:46:05ZengElsevierJournal of Cardiovascular Magnetic Resonance1097-66472025-01-0127110187310.1016/j.jocmr.2025.101873Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imagingAndrew Phair0René M. Botnar1Claudia Prieto2School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United KingdomSchool of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom; Escuela de Ingeniería, Pontifica Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile; Instituto de Ingeniería Biológica y Médica, Pontifica Universidad Católica de Chile, Santiago, Chile; Technical University of Munich, Institute of Advanced Study, Munich, GermanySchool of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom; Escuela de Ingeniería, Pontifica Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile; Corresponding author at: School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ABSTRACT: Achieving sufficient spatial and temporal resolution for dynamic applications in cardiovascular magnetic resonance (CMR) imaging is a challenging task due to the inherently slow nature of CMR. In order to accelerate scans and allow improved resolution, much research over the past three decades has been aimed at developing innovative reconstruction methods that can yield high-quality images from reduced amounts of k-space data. In this review, we describe the evolution of these reconstruction techniques, with a particular focus on those advances that have shifted the dynamic reconstruction paradigm as it relates to CMR. This review discusses and explains the fundamental ideas behind the success of modern reconstruction algorithms, including parallel imaging, spatio-temporal redundancies, compressed sensing, low-rank methods and machine learning.http://www.sciencedirect.com/science/article/pii/S1097664725000353Dynamic cardiac MRIMRI cineMRI reconstructionParallel imagingSpatio-temporal redundancyCompressed sensing |
| spellingShingle | Andrew Phair René M. Botnar Claudia Prieto Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging Journal of Cardiovascular Magnetic Resonance Dynamic cardiac MRI MRI cine MRI reconstruction Parallel imaging Spatio-temporal redundancy Compressed sensing |
| title | Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| title_full | Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| title_fullStr | Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| title_full_unstemmed | Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| title_short | Reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| title_sort | reconstruction techniques for accelerating dynamic cardiovascular magnetic resonance imaging |
| topic | Dynamic cardiac MRI MRI cine MRI reconstruction Parallel imaging Spatio-temporal redundancy Compressed sensing |
| url | http://www.sciencedirect.com/science/article/pii/S1097664725000353 |
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