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Massively parallel CUDA simulations of cardiac and embryonic MRI on a cloud-based cluster
dc.creator | Kantasis G., Xanthis C.G., Haris K., Aletras A.H. | en |
dc.date.accessioned | 2023-01-31T08:30:18Z | |
dc.date.available | 2023-01-31T08:30:18Z | |
dc.date.issued | 2015 | |
dc.identifier | 10.1109/CIC.2015.7408688 | |
dc.identifier.isbn | 9781509006854 | |
dc.identifier.issn | 23258861 | |
dc.identifier.uri | http://hdl.handle.net/11615/74294 | |
dc.description.abstract | Embryonic and cardiovascular Magnetic Resonance Imaging (MRI) in both clinic and research environments is confronted by challenges like motion, flow and low resolution. MRI simulations can be used as a valuable tool against these challenges but they are characterized by high computational intensity. In this study we implemented cardiac and embryonic MR simulations on a cloud-based cluster. For this purpose, an anatomical model of a human embryo was split over a variable number of computer nodes on the cloud. Simulation of a Gradient-Echo pulse sequence was performed and the partial results were aggregated in a central node to produce the simulated MR image, following the MapReduce paradigm. The measured execution times and speedups demonstrated the benefits of this cloud-based approach. © 2015 CCAL. | en |
dc.language.iso | en | en |
dc.source | Computing in Cardiology | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964066818&doi=10.1109%2fCIC.2015.7408688&partnerID=40&md5=bb371b786b160acf773479dc0b20962d | |
dc.subject | Cardiology | en |
dc.subject | Anatomical modeling | en |
dc.subject | Cardiovascular magnetic resonance imaging | en |
dc.subject | Computational intensity | en |
dc.subject | Massively parallels | en |
dc.subject | MRI simulation | en |
dc.subject | Partial results | en |
dc.subject | Research environment | en |
dc.subject | Variable number | en |
dc.subject | Magnetic resonance imaging | en |
dc.subject | IEEE Computer Society | en |
dc.title | Massively parallel CUDA simulations of cardiac and embryonic MRI on a cloud-based cluster | en |
dc.type | conferenceItem | en |
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