Article

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. and Rueckert, D. (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. and Rueckert, D. (2018). Automated cardiovascular magnetic resonance image analysis with fully convolutional networks. Journal of Cardiovascular Magnetic Resonance, 20, 65.. doi: 10.1186/s12968-018-0471-x

Book Section

Al-Arif, S. M., Gundry, M., Knapp, K. and Slabaugh, G. G. (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. and Li, S. (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. ISBN 978-3-319-55049-7