R. Davies

发表

A Multicenter, Scan-Rescan, Human and Machine Learning CMR Study to Test Generalizability and Precision in Imaging Biomarker Analysis.

D. Rueckert, A. Hughes, Wenjia Bai, 2019, Circulation. Cardiovascular imaging.

Repeatability of Cardiac Magnetic Resonance Radiomics: A Multi-Centre Multi-Vendor Test-Retest Study

P. Munroe, S. Petersen, J. Moon, 2020, Frontiers in Cardiovascular Medicine.

University of Birmingham Variation in cardiovascular magnetic resonance myocardial contouring

J. Moon, R. Steeds, L. Hudsmith, 2019 .

The Prognostic Significance of Quantitative Myocardial Perfusion: An Artificial Intelligence Based Approach Using Perfusion Mapping

P. Kellman, S. Plein, S. Petersen, 2020 .

Immune boosting by B.1.1.529 (Omicron) depends on previous SARS-CoV-2 exposure

Lauren M. Hickling, A. Hingorani, Tom Coleman, 2022, Science.

Healthcare Workers Bioresource: Study outline and baseline characteristics of a prospective healthcare worker cohort to study immune protection and pathogenesis in COVID-19

Lauren M. Hickling, A. Hingorani, S. Petersen, 2020, Wellcome open research.

Healthcare Workers Bioresource: Study outline and baseline characteristics of a prospective healthcare worker cohort to study immune protection and pathogenesis in COVID-19.

Lauren M. Hickling, A. Hingorani, S. Petersen, 2020, Wellcome open research.

Hypertrophic cardiomyopathy: insights from extracellular volume mapping.

P. Kellman, J. Moon, C. Manisty, 2021, European journal of preventive cardiology.

Phenotyping hypertrophic cardiomyopathy using cardiac diffusion magnetic resonance imaging: the relationship between microvascular dysfunction and microstructural changes

P. Kellman, S. Plein, I. Teh, 2021, European heart journal. Cardiovascular Imaging.

Prospective Case-Control Study of Cardiovascular Abnormalities 6 Months Following Mild COVID-19 in Healthcare Workers

P. Kellman, E. Schelbert, J. Moon, 2021, JACC: Cardiovascular Imaging.

Prognostic Value of Pulmonary Transit Time and Pulmonary Blood Volume Estimation Using Myocardial Perfusion CMR

A. Hughes, P. Kellman, S. Petersen, 2021, JACC. Cardiovascular imaging.

Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2

Lauren M. Hickling, Steffen E. Petersen, A. Hingorani, 2021, Nature.

Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning

D. Rueckert, P. Kellman, Wenjia Bai, 2022, Journal of Cardiovascular Magnetic Resonance.

Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization.

P. Kellman, C. Manisty, G. Cole, 2022, Journal of the American College of Cardiology.

Apical Ischemia Is a Universal Feature of Apical Hypertrophic Cardiomyopathy

P. Kellman, G. Captur, W. McKenna, 2023, Circulation. Cardiovascular imaging.

Myocardial Involvement After Hospitalization for COVID-19 Complicated by Troponin Elevation: A Prospective, Multicenter, Observational Study

P. Macfarlane, S. Piechnik, V. Ferreira, 2023, Circulation.

Variation in cardiovascular magnetic resonance myocardial contouring: Insights from an international survey

J. Moon, R. Steeds, L. Hudsmith, 2019, Journal of magnetic resonance imaging : JMRI.

Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.

G. Pontone, S. Petersen, B. Gerber, 2020, The Lancet. Digital health.

Landmark Detection in Cardiac MRI by Using a Convolutional Neural Network

Peter Kellman, Hui Xue, Marianna Fontana, 2021, Radiology. Artificial intelligence.

Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning

P. Kellman, S. Plein, J. Moon, 2019, Radiology. Artificial intelligence.

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Daniel Rueckert, Chen Chen, Wenjia Bai, 2019, Frontiers in Cardiovascular Medicine.

Use of quantitative cardiovascular magnetic resonance myocardial perfusion mapping for characterization of ischemia in patients with left internal mammary coronary artery bypass grafts

P. Kellman, J. Moon, C. Manisty, 2021, Journal of Cardiovascular Magnetic Resonance.

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar

Marco S. Nobile, D. Besozzi, P. Kellman, 2022, Comput. Methods Programs Biomed..

Study protocol: MyoFit46—the cardiac sub-study of the MRC National Survey of Health and Development

P. Lambiase, P. Kellman, M. Orini, 2022, BMC Cardiovascular Disorders.

Maximal Wall Thickness Measurement in Hypertrophic Cardiomyopathy: Biomarker Variability and its Impact on Clinical Care.

S. Petersen, R. Kwong, P. Nihoyannopoulos, 2021, JACC. Cardiovascular imaging.

Maximal Wall Thickness Measurement in Hypertrophic Cardiomyopathy

S. Petersen, R. Kwong, P. Nihoyannopoulos, 2022 .

The Prognostic Significance of Quantitative Myocardial Perfusion

P. Kellman, S. Plein, S. Petersen, 2020, Circulation.

Association of Myocardial Fibrosis and Stroke Volume by Cardiovascular Magnetic Resonance in Patients With Severe Aortic Stenosis With Outcome After Valve Replacement: The British Society of Cardiovascular Magnetic Resonance AS700 Study.

M. Dweck, J. Moon, J. Greenwood, 2022, JAMA cardiology.

Myocardial Perfusion Imaging After Severe COVID-19 Infection Demonstrates Regional Ischemia Rather Than Global Blood Flow Reduction

P. Kellman, C. Manisty, G. Cole, 2021, Frontiers in Cardiovascular Medicine.

A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning

D. Alexander, S. Wan, L. Menezes, 2021, IEEE Access.

Diagnostic performance of virtual fractional flow reserve derived from routine coronary angiography using segmentation free reduced order (1-dimensional) flow modelling

P. Nithiarasu, J. Mynard, J. Halcox, 2020, JRSM cardiovascular disease.

Deep learning in congenital heart disease imaging: hope but not haste

S. Babu-Narayan, R. Davies, 2020, Heart.

Automated In‐Line Artificial Intelligence Measured Global Longitudinal Shortening and Mitral Annular Plane Systolic Excursion: Reproducibility and Prognostic Significance

P. Kellman, E. Schelbert, T. Wong, 2022, Journal of the American Heart Association.

Machine Learning for ECG Diagnosis of LV Dysfunction.

R. Davies, Aled R. C. Jones, 2021, JACC. Cardiovascular imaging.

Artificial intelligence in medical device software and high-risk medical devices – a review of definitions, expert recommendations and regulatory initiatives

F. Rademakers, N. Bruining, E. Caiani, 2023, Expert review of medical devices.

The mechanical and perfusion basis of exercise limitation in apical hypertrophic cardiomyopathy

P. Kellman, G. Captur, Lopes, 2023, medRxiv.

Evaluating semi-supervision methods for medical image segmentation: applications in cardiac magnetic resonance imaging

Christopher Ré, Sen Wu, P. Kellman, 2023, Journal of medical imaging.

A 3D deep learning classifier and its explainability when assessing coronary artery disease

Daniel C. Alexander, L. Menezes, A. Nair, 2023, ArXiv.

Microstructural and Microvascular Phenotype of Sarcomere Mutation Carriers and Overt Hypertrophic Cardiomyopathy

P. Lambiase, P. Macfarlane, P. Kellman, 2023, Circulation.

Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging

P. Kellman, H. Xue, R. Davies, 2022, European Heart Journal - Cardiovascular Imaging.

Myocardial scar and remodelling predict long-term mortality in severe aortic stenosis beyond 10 years

G. Captur, T. Treibel, Anvesha Singh, 2024, European heart journal.

Global myocardial ischaemia in severe aortic stenosis reverses early after aortic valve replacement

P. Kellman, C. Manisty, G. Thornton, 2023, European Heart Journal - Cardiovascular Imaging.

Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study.

Clemens P. Spielvogel, T. Treibel, J. Mascherbauer, 2024, The Lancet. Digital health.

Improved Diagnostic Criteria for Apical Hypertrophic Cardiomyopathy.

P. Kellman, C. Manisty, G. Captur, 2023, JACC. Cardiovascular imaging.