Computational study of aortic hemodynamics for patients with an abnormal aortic valve: The importance of secondary flow at the ascending aorta inlet von Pirola, S., Jarral, O. A., O'Regan, D. P., Asimakopoulos, G., Anderson, J. R., Pepper, J. R., Athanasiou, T., Xu, X. Y.

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Putting machine learning into motion: applications in cardiovascular imaging von O'Regan, D.P.

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On the choice of outlet boundary conditions for patient-specific analysis of aortic flow using computational fluid dynamics von Pirola, S, Cheng, Z, Jarral, O.A, O'Regan, D.P, Pepper, J.R, Athanasiou, T, Xu, X.Y

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Automated detection of enteric tubes misplaced in the respiratory tract on chest radiographs using deep learning with two centre validation von Mallon, D H, McNamara, C D, Rahmani, G S, O'Regan, D P, Amiras, D G

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A comparison of MR cholangiopancreatography at 1.5 and 3.0 Tesla von O'REGAN, D. P, FITZGERALD, J, ALLSOP, J, GIBSON, D, LARKMAN, D. J, COKKINOS, D, HAJNAL, J. V, SCHMITZ, S. A

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Identifying the optimal regional predictor of right ventricular global function: a high‐resolution three‐dimensional cardiac magnetic resonance study von Dawes, T. J. W., de Marvao, A., Shi, W., Rueckert, D., Cook, S. A., O'Regan, D. P.

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White Matter Brain Lesions in Midlife Familial Hypercholesterolemic Patients at 3-Tesla Magnetic Resonance Imaging von Schmitz, S. A., O'Regan, D. P., Fitzpatrick, J., Neuwirth, C., Potter, E., Tosi, I., Hajnal, J. V., Naoumova, R. P.

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Acute myocardial infarction: susceptibility-weighted cardiac MRI for the detection of reperfusion haemorrhage at 1.5 T von Durighel, G, Tokarczuk, P.F, Karsa, A, Gordon, F, Cook, S.A, O'Regan, D.P

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Genetic and phenotypic architecture of biventricular trabeculation von Mcgurk, K, Ware, J S, O'regan, D P

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Establishing a clinical cardiac MRI service von O'Regan, D.P., Schmitz, S.A.

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A Probabilistic Patch-Based Label Fusion Model for Multi-Atlas Segmentation With Registration Refinement: Application to Cardiac MR Images von Wenjia Bai, Wenzhe Shi, O'Regan, D. P., Tong Tong, Haiyan Wang, Jamil-Copley, S., Peters, N. S., Rueckert, D.

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Putting machine learning into motion: applications in cardiovascular imaging von O'Regan, DP

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Can machine learning predict cardiac risk using mammography? von Lip, G, O'Regan, DP

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DeepMesh: mesh-based cardiac motion tracking using deep learning von Meng, Q, Bai, W, O'Regan, DP, Rueckert, D

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Polygenic risk score for hypertrophic cardiomyopathy predicts population disease risk, penetrance in sarcomeric rare variant carriers and survival in cases von Zheng, S, Jurgens, S J, Mcgurk, K A, Grace, C, Francis, C, De Marvao, A, Halliday, B P, Prasad, S K, Barton, P J R, O'regan, D P, Tadros, R, Goel, A, Watkins, H, Bezzina, C R, Ware, J S

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Bariatric surgery reverses ventricular repolarisation heterogeneity in obesity: mechanistic insights into fat-related arrhythmic risk von Patel, K, Bajaj, N, Statton, B, Li, X, Herath, N S, Nyamakope, K, Davidson, R, Stoks, J, Purkayastha, S, Ware, J S, O'Regan, D P, Lambiase, P D, Cluitmans, M, Peters, N S, Ng, F S

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TR 55: Design guidance for stengthening concrete structures using fibre composite materials: a review von Arya, C., Clarke, J.L., Kay, E.A., O’Regan, P.D.

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Novel insights into cardiovascular ageing in the general population using machine learning von Shah, M, H De A Inacio, M, Lu, C, Schiratti, P R, Zheng, S L, Clement, A, Bai, W, King, A, Ware, J S, Wilkins, M R, Kryukov, I, Mcgurk, K, Bender, C, Freitag, D, O'regan, D P

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Assessment of severe reperfusion injury with T2 cardiac MRI in patients with acute myocardial infarction von O'Regan, Declan P, Ariff, Ben, Neuwirth, Clare, Tan, Yvonne, Durighel, Giuliana, Cook, Stuart A

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Stiff Arteries, Stiff Ventricles: Correlation or Causality in Heart Failure? von O'Regan, DP

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