Items where Author is "Glocker, B."
Article
Tarroni, G. 
ORCID: 0000-0002-0341-6138, Bai, W., Oktay, O. , Schuh, A., Suzuki, H., Glocker, B., Matthews, P. M. & Rueckert, D. (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. (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. (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
Book Section
Al-Arif, S. M., Gundry, M., Knapp, K. & 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. & 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.
Conference or Workshop Item
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. (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