Zobrazeno 1 - 10
of 307
pro vyhledávání: '"Reza, Nezafat"'
Autor:
Manuel A. Morales, Siyeop Yoon, Ahmed Fahmy, Fahime Ghanbari, Shiro Nakamori, Jennifer Rodriguez, Jennifer Yue, Jordan A. Street, Daniel A. Herzka, Warren J. Manning, Reza Nezafat
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 25, Iss 1, Pp 1-14 (2023)
Abstract Background Exercise cardiovascular magnetic resonance (Ex-CMR) myocardial tagging would enable quantification of myocardial deformation after exercise. However, current electrocardiogram (ECG)-segmented sequences are limited for Ex-CMR. Meth
Externí odkaz:
https://doaj.org/article/05fc8f8b55a7454cb123e18de25084f5
Autor:
Constantin-Cristian Topriceanu, Massimiliano Fornasiero, Han Seo, Matthew Webber, Kathryn E. Keenan, Karl F. Stupic, Rüdiger Bruehl, Bernd Ittermann, Kirsty Price, Louise McGrath, Wenjie Pang, Alun D. Hughes, Reza Nezafat, Peter Kellman, Iain Pierce, James C. Moon, Gabriella Captur
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 25, Iss 1, Pp 1-14 (2023)
Abstract Introduction A long T2 relaxation time can reflect oedema, and myocardial inflammation when combined with increased plasma troponin levels. Cardiovascular magnetic resonance (CMR) T2 mapping therefore has potential to provide a key diagnosti
Externí odkaz:
https://doaj.org/article/caef70cde30d4ae6831d1421826c142d
Autor:
Manuel A. Morales, Salah Assana, Xiaoying Cai, Kelvin Chow, Hassan Haji-valizadeh, Eiryu Sai, Connie Tsao, Jason Matos, Jennifer Rodriguez, Sophie Berg, Neal Whitehead, Patrick Pierce, Beth Goddu, Warren J. Manning, Reza Nezafat
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 24, Iss 1, Pp 1-14 (2022)
Abstract Background Exercise cardiovascular magnetic resonance (Ex-CMR) is a promising stress imaging test for coronary artery disease (CAD). However, Ex-CMR requires accelerated imaging techniques that result in significant aliasing artifacts. Our g
Externí odkaz:
https://doaj.org/article/192e7a7a898a48f69ab77be6ee77795c
Autor:
Ahmed S. Fahmy, Ethan J. Rowin, Arghavan Arafati, Talal Al-Otaibi, Martin S. Maron, Reza Nezafat
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 24, Iss 1, Pp 1-12 (2022)
Abstract Background Myocardial scar burden quantified using late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR), has important prognostic value in hypertrophic cardiomyopathy (HCM). However, nearly 50% of HCM patients have no sc
Externí odkaz:
https://doaj.org/article/53457c605f7841a88108fec802553690
Autor:
Rui Guo, Hossam El-Rewaidy, Salah Assana, Xiaoying Cai, Amine Amyar, Kelvin Chow, Xiaoming Bi, Tuyen Yankama, Julia Cirillo, Patrick Pierce, Beth Goddu, Long Ngo, Reza Nezafat
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 24, Iss 1, Pp 1-15 (2022)
Abstract Purpose To develop and evaluate MyoMapNet, a rapid myocardial T1 mapping approach that uses fully connected neural networks (FCNN) to estimate T1 values from four T1-weighted images collected after a single inversion pulse in four heartbeats
Externí odkaz:
https://doaj.org/article/2485caf3bef74e0d88ef27b1abb148be
Autor:
Gabriella Captur, Abhiyan Bhandari, Rüdiger Brühl, Bernd Ittermann, Kathryn E. Keenan, Ye Yang, Richard J. Eames, Giulia Benedetti, Camilla Torlasco, Lewis Ricketts, Redha Boubertakh, Nasri Fatih, John P. Greenwood, Leonie E. M. Paulis, Chris B. Lawton, Chiara Bucciarelli-Ducci, Hildo J. Lamb, Richard Steeds, Steve W. Leung, Colin Berry, Sinitsyn Valentin, Andrew Flett, Charlotte de Lange, Francesco DeCobelli, Magalie Viallon, Pierre Croisille, David M. Higgins, Andreas Greiser, Wenjie Pang, Christian Hamilton-Craig, Wendy E. Strugnell, Tom Dresselaers, Andrea Barison, Dana Dawson, Andrew J. Taylor, François-Pierre Mongeon, Sven Plein, Daniel Messroghli, Mouaz Al-Mallah, Stuart M. Grieve, Massimo Lombardi, Jihye Jang, Michael Salerno, Nish Chaturvedi, Peter Kellman, David A. Bluemke, Reza Nezafat, Peter Gatehouse, James C. Moon, on behalf of the T1MES Consortium
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 22, Iss 1, Pp 1-17 (2020)
Abstract Background The T 1 Mapping and Extracellular volume (ECV) Standardization (T1MES) program explored T 1 mapping quality assurance using a purpose-developed phantom with Food and Drug Administration (FDA) and Conformité Européenne (CE) regul
Externí odkaz:
https://doaj.org/article/82247d58bee943b7b64d256bcf989b3c
Autor:
Tim Leiner, Daniel Rueckert, Avan Suinesiaputra, Bettina Baeßler, Reza Nezafat, Ivana Išgum, Alistair A. Young
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 21, Iss 1, Pp 1-14 (2019)
Abstract Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers i
Externí odkaz:
https://doaj.org/article/50fded3c0a6f4833a5d28092b3bf1e51
Autor:
John Whitaker, Radhouene Neji, Nicholas Byrne, Esther Puyol-Antón, Rahul K. Mukherjee, Steven E. Williams, Henry Chubb, Louisa O’Neill, Orod Razeghi, Adam Connolly, Kawal Rhode, Steven Niederer, Andrew King, Cory Tschabrunn, Elad Anter, Reza Nezafat, Martin J. Bishop, Mark O’Neill, Reza Razavi, Sébastien Roujol
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 21, Iss 1, Pp 1-15 (2019)
Abstract Background Ex-vivo cardiovascular magnetic resonance (CMR) imaging has played an important role in the validation of in-vivo CMR characterization of pathological processes. However, comparison between in-vivo and ex-vivo imaging remains chal
Externí odkaz:
https://doaj.org/article/74754297b562494da7bb5cf1beb070a1
Autor:
Hassan Haji-Valizadeh, Rui Guo, Selcuk Kucukseymen, Yankama Tuyen, Jennifer Rodriguez, Amanda Paskavitz, Patrick Pierce, Beth Goddu, Long H. Ngo, Reza Nezafat
Publikováno v:
Frontiers in Physics, Vol 9 (2021)
Propose: The purpose of this study was to compare the performance of deep learning networks trained with complex-valued and magnitude images in suppressing the aliasing artifact for highly accelerated real-time cine MRI.Methods: Two 3D U-net models (
Externí odkaz:
https://doaj.org/article/043e36fee06a462280fba30bd6c972d9
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
Background: Development of advanced heart failure (HF) symptoms is the most common adverse pathway in hypertrophic cardiomyopathy (HCM) patients. Currently, there is a limited ability to identify HCM patients at risk of HF.Objectives: In this study,
Externí odkaz:
https://doaj.org/article/9c9ada663c2c497bbebde76a39ffdae0