Ensemble of deep convolutional neural networks with Monte Carlo dropout sampling for automated image segmentation quality control and robust deep learning using small datasets by Hann, E, Gonzales, RA, Popescu, IA, Zhang, Q, Ferreira, VM, Piechnik, SK

Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping by Hann, E, Popescu, IA, Gonzales, RA, Zhang, Q, Barutçu, A, Neubauer, S, Ferreira, VM, Piechnik, SK

Development of deep learning virtual native enhancement for gadolinium-free myocardial infarction and viability assessment by Zhang, Q, Burrage, MK, Shanmuganathan, M, Gonzales, RA, Nikolaidou, C, Popescu, IA, Lukaschuk, E, Neubauer, S, Ferreira, VM, Piechnik, SK

Cardiac stress T1-mapping response and extracellular volume stability of MOLLI-based T1-mapping methods by Burrage, MK, Shanmuganathan, M, Zhang, Q, Hann, E, Popescu, IA, Soundarajan, R, Chow, K, Neubauer, S, Ferreira, VM, Piechnik, SK

MOCOnet: robust motion correction of cardiovascular magnetic resonance T1 mapping using convolutional neural networks by Gonzales, RA, Zhang, Q, Papież, BW, Werys, K, Lukaschuk, E, Popescu, IA, Burrage, MK, Shanmuganathan, M, Ferreira, VM, Piechnik, SK

Fast and robust motion correction of cardiovascular magnetic resonance T1-mapping using data-driven convolutional neural networks for generalisability by Gonzales, RA, Zhang, Q, Papież, BW, Werys, K, Lukaschuk, E, Popescu, IA, Burrage, MK, Shanmuganathan, M, Ferreira, VM, Piechnik, SK

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images by Gonzales, RA, Ibáñez, DH, Hann, E, Popescu, IA, Burrage, MK, Lee, YP, Altun, İ, Weintraub, WS, Kwong, RY, Kramer, CM, Neubauer, S, Ferreira, VM, Zhang, Q, Piechnik, SK

Quality control-driven framework for reliable automated segmentation of cardiac magnetic resonance LGE and VNE images by Gonzales, RA, Ibáñez, DH, Hann, E, Popescu, IA, Burrage, MK, Lee, YP, Altun, İ, Weintraub, WS, Kwong, RY, Kramer, CM, Neubauer, S, Ferreira, VM, Zhang, Q, Piechnik, SK

Quality control-driven image segmentation towards reliable automatic image analysis in large-scale cardiovascular magnetic resonance aortic cine imaging by Hann, E, Biasiolli, L, Zhang, Q, Popescu, IA, Werys, K, Lukaschuk, E, Carapella, V, Paiva, JM, Aung, N, Rayner, JJ, Fung, K, Puchta, H, Sanghvi, MM, Moon, NO, Thomas, KE, Ferreira, VM, Petersen, SE, Neubauer, S, Piechnik, SK

Artificial intelligence for contrast-free MRI: scar assessment in myocardial infarction using deep learning–based virtual native enhancement by Zhang, Q, Burrage, MK, Shanmuganathan, M, Gonzales, RA, Lukaschuk, E, Thomas, KE, Mills, R, Leal Pelado, J, Nikolaidou, C, Popescu, IA, Lee, YP, Zhang, X, Dharmakumar, R, Myerson, SG, Rider, O, Channon, KM, Neubauer, S, Piechnik, SK, Ferreira, VM

Toward replacing late gadolinium enhancement with artificial intelligence virtual native enhancement for gadolinium-free cardiovascular magnetic resonance tissue characterization i... by Zhang, Q, Burrage, MK, Lukaschuk, E, Shanmuganathan, M, Popescu, IA, Nikolaidou, C, Mills, R, Werys, K, Hann, E, Barutcu, A, Polat, SD, Salerno, M, Jerosch-Herold, M, Kwong, RY, Watkins, HC, Kramer, CM, Neubauer, S, Ferreira, VM, Piechnik, SK