Search Results - "Vimalesvaran, K"

Late gadolinium enhancement following Covid-19 infection does not predict outcome: a single-centre study by Vimalesvaran, K, Howard, J P, Zaman, S, Ariff, B, Bharath, A A, Cole, G

“…Abstract Background Some patients are found to have myocardial scarring after infection with coronavirus-2019 disease (COVID-19) as evidenced by the presence…”
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Machine learning can accurately detect abnormal aortic valves in CMR by Vimalesvaran, K, Uslu, F, Zaman, S, Howard, J, Bharath, A, Cole, G

“…Abstract Background Improving the efficiency of CMR by acquiring fewer, and more targeted sequences, would improve the diagnostic yield and reduce patient…”
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P5572Percutaneous edge-to-edge repair for the treatment of acute decompensated severe mitral regurgitation: a single-centre experience by Vimalesvaran, K, Kelly, L, Vazir, A, Smith, R

“…Abstract Background Patients with acute, decompensated severe mitral regurgitation (MR) are poorly served by surgical or medical treatments and is associated…”
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An artificial intelligence-based landmark model for early detection of aortic stenosis in Cardiac MRI by Vimalesvaran, K, Sanchez, A, Zaman, S, Galazis, C, Varela, M, Linton, N, Howard, J P, Cole, G D, Bharath, A A

“…Abstract Background The utilisation of ratiometric intensity measures from cardiac magnetic resonance imaging (CMR) offers a promising biomarker for the…”
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Ratio of aortic to left ventricle SSFP blood signal in a single 3-chamber view correlates with aortic stenosis severity by Vimalesvaran, K, Zaman, S, Howard, J P, Zehra, F, Ariff, B, Bharath, A, Cole, G D

“…Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): UK research and Innovation [UKRI Centre for Doctoral…”
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2D Echocardiographic aortic root dimensions and longitudinal analysis with artificial intelligence using an open dataset from a UK-wide collaborative by Ng, T, Hannan, S H, Julea, M, Singh, A, Zetani, M, Vimalesvaran, K, Tawil, M, Rana, B, Demetrescu, C, Ghosh, A, Sehmi, J, Bhattacharyya, S, Stowell, C, Shun-Shin, M J, Francis, D P

“…Abstract Background Surveillance of aortic dimensions requires reproducible measurements, and knowledge of the rate of progression in those with dilatation…”
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Prognostic assessment following acute myocarditis requires convalescent scanning: neither peak troponin nor index scan T2 signal predicts convalescent late gadolinium enhancement by Zaman, S, Vimalesvaran, K, Johns, I, Howard, JP, Cole, GD

“…Abstract Funding Acknowledgements Type of funding sources: None. Background Cardiovascular magnetic resonance (CMR) is a key diagnostic investigation in acute…”
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automatic detection of aortic valve pathology using 3-chamber cine MRI by On, Y, Vimalesvaran, K, Galazis, C, Zaman, S, Howard, J, Linton, N, Peters, N, Cole, G, Bharath, A A, Varela, M

“…Abstract Funding Acknowledgements Type of funding sources: None. Introduction The assessment of aortic valve pathology using magnetic resonance imaging (MRI)…”
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Fully automated global longitudinal strain assessment using artificial intelligence developed and validated by a UK-wide echocardiography expert collaborative by Stowell, C, Howard, J, Demetrescu, C, Bhattacharyya, S, Mangion, K, Vimalesvaran, K, Cole, G, Rajani, R, Sehmi, J, Alzetani, M, Zolgharni, M, Rana, B, Francis, D, Shun-Shin, M

“…Abstract Background Left ventricular longitudinal strain has been reported to deliver reproducibility, sensitivity and prognostic value over and above ejection…”
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Automated left ventricular dimension assessment using artificial intelligence by Stowell, C, Howard, J, Cole, G, Ananthan, K, Demetrescu, C, Pearce, K, Rajani, R, Sehmi, J, Vimalesvaran, K, Kanaganayagam, S, Ghosh, A, Chambers, J, Rana, B, Francis, D, Shun-Shin, M

“…Abstract Background and purpose Artificial intelligence (AI) has the potential to greatly improve efficiency and reproducibility of quantification in…”
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Framework for large-scale automatic curation of heterogeneous cardiac MRI (ACUR MRI) by Galazis, C, Vimalesvaran, K, Zaman, S, Petri, C, Howard, J, Linton, N, Peters, N, Cole, G, Bharath, AA, Varela, M

“…Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UKRI CDT in AI for Healthcare…”
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Myocardial perfusion after COVID-19 infection: No persisting impaired myocardial blood flow in surviving patients by Thornton, G, Shetye, A, Knott, K, Razvi, Y, Vimalesvaran, K, Kurdi, H, Artico, J, Yousef, S, Antonakaki, D, Kellman, P, Knight, D, Cole, GD, Moon, JC, Fontana, M, Treibel, TA

“…Abstract Funding Acknowledgements Type of funding sources: None. Background  Acute myocardial damage is common in hospitalized patients with severe COVID-19,…”
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Role of rivaroxaban in the management of atrial fibrillation: insights from clinical practice by Vimalesvaran, Kavitha, Dockrill, Seth J, Gorog, Diana A

“…Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and it leads to significant morbidity and mortality, predominantly from ischemic…”
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Classification of Mitral Regurgitation from Cardiac Cine MRI using Clinically-Interpretable Morphological Features by On, Y, Vimalesvaran, K, Zaman, S, Shun-Shin, M, Howard, J, Linton, N, Cole, G, Bharath, A. A, Varela, M

“…The assessment of mitral regurgitation (MR) using cardiac MRI, particularly Cine MRI, is a promising technique due to its wide availability. However, some of…”
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Automatic Aortic Valve Pathology Detection from 3-Chamber Cine MRI with Spatio-Temporal Attention Maps by On, Y, Vimalesvaran, K, Galazis, C, Zaman, S, Howard, J, Linton, N, Peters, N, Cole, G, Bharath, A. A, Varela, M

“…The assessment of aortic valve pathology using magnetic resonance imaging (MRI) typically relies on blood velocity estimates acquired using phase contrast (PC)…”
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