City Research Online

Lekadir, K. ORCID: 0000-0002-9456-1612, Frangi, A. F., Porras, A. R. , Glocker, B., Cintas, C., Langlotz, C. P., Weicken, E., Asselbergs, F. W., Prior, F., Collins, G. S., Kaissis, G., Tsakou, G., Buvat, I., Kalpathy-Cramer, J., Mongan, J., Schnabel, J. A., Kushibar, K., Riklund, K., Marias, K., Amugongo, L. M., Fromont, L. A., Maier-Hein, L., Cerdá-Alberich, L., Martí-Bonmatí, L., Cardoso, M. J., Bobowicz, M., Shabani, M., Tsiknakis, M., Zuluaga, M. A., Fritzsche, M-C., Camacho, M., Linguraru, M. G., Wenzel, M., De Bruijne, M., Tolsgaard, M. G., Goisauf, M., Cano Abadía, M., Papanikolaou, N., Lazrak, N., Pujol, O., Osuala, R., Napel, S., Colantonio, S., Joshi, S., Klein, S., Aussó, S., Rogers, W. A., Salahuddin, Z., Starmans, M. P. A., FUTURE-AI Consortium & Botwe, B. O. ORCID: 0000-0002-0477-640Xview all authors (2025). FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare. BMJ, 388, article number e081554. doi: 10.1136/bmj-2024-081554

Wang, S., Tarroni, G. ORCID: 0000-0002-0341-6138, Qin, C. , Mo, Y., Dai, C., Chen, C., Glocker, B., Guo, Y., Rueckert, D. & Bai, W.view all authors (2020). Deep Generative Model-based Quality Control for Cardiac MRI Segmentation. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 04 - 08 October 2020, Lima, Peru. doi: 10.1007/978-3-030-59719-1_9

Tarroni, G. ORCID: 0000-0002-0341-6138, Bai, W., Oktay, O. , Schuh, A., Suzuki, H., Glocker, B., Matthews, P. M. & Rueckert, D.view all authors (2020). Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank. Scientific Reports, 10(1), article number 2408. doi: 10.1038/s41598-020-58212-2

Tarroni, G. ORCID: 0000-0002-0341-6138, Oktay, O., Bai, W. , Schuh, A., Suzuki, H., Passerat-Palmbach, J., De Marvao, A., O’Regan, D. P., Cook, S., Glocker, B., Matthews, P M. & Rueckert, D.view all authors (2019). Learning-based quality control for cardiac MR images. IEEE Transactions on Medical Imaging, 38(5), pp. 1127-1138. doi: 10.1109/tmi.2018.2878509

Bai, W., Sinclair, M., Tarroni, G. ORCID: 0000-0002-0341-6138 , Oktay, O., Rajchl, M., Vaillant, G., Lee, A. M., Aung, N., Lukaschuk, E., Sanghvi, M. M., Zemrak, F., Fung, K., Paiva, J. M., Carapella, V., Kim, Y. J., Suzuki, H., Kainz, B., Matthews, P M., Petersen, S. E., Piechnik, S. K., Neubauer, S., Glocker, B. & Rueckert, D.view all authors (2018). Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. Journal of Cardiovascular Magnetic Resonanc, 20(1), article number 65. doi: 10.1186/s12968-018-0471-x

Al-Arif, S. M., Gundry, M., Knapp, K. & Slabaugh, G. G.view all authors (2017). Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae. In: Yao, J., Vrtovec, T., Zheng, G. , Frangi, A., Glocker, B. & Li, S.view all authors (Eds.), Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae. Lecture Notes in Computer Science, 10182. (pp. 3-15). Cham: Springer.