| Usad: Unsupervised anomaly detection on multivariate time series J Audibert, P Michiardi, F Guyard, S Marti, MA Zuluaga Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 946 | 2020 |
| Interactive medical image segmentation using deep learning with image-specific fine tuning G Wang, W Li, MA Zuluaga, R Pratt, PA Patel, M Aertsen, T Doel, ... IEEE transactions on medical imaging 37 (7), 1562-1573, 2018 | 933 | 2018 |
| DeepIGeoS: a deep interactive geodesic framework for medical image segmentation G Wang, MA Zuluaga, W Li, R Pratt, PA Patel, M Aertsen, T Doel, ... IEEE transactions on pattern analysis and machine intelligence 41 (7), 1559-1572, 2018 | 490 | 2018 |
| Right ventricle segmentation from cardiac MRI: a collation study C Petitjean, MA Zuluaga, W Bai, JN Dacher, D Grosgeorge, J Caudron, ... Medical image analysis 19 (1), 187-202, 2015 | 269 | 2015 |
| Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets C Tobon-Gomez, AJ Geers, J Peters, J Weese, K Pinto, R Karim, ... IEEE Transactions on Medical Imaging 34 (7), 1460 - 1473, 2015 | 218 | 2015 |
| Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian–Eulerian PDE approach using partial volume maps O Acosta, P Bourgeat, MA Zuluaga, J Fripp, O Salvado, S Ourselin, ... Medical image analysis 13 (5), 730-743, 2009 | 120 | 2009 |
| Multi-atlas propagation whole heart segmentation from MRI and CTA using a local normalised correlation coefficient criterion MA Zuluaga, MJ Cardoso, M Modat, S Ourselin International Conference on Functional Imaging and Modeling of the Heart …, 2013 | 112 | 2013 |
| Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading K Hameeteman, MA Zuluaga, M Freiman, L Joskowicz, O Cuisenaire, ... Medical image analysis 15 (4), 477-488, 2011 | 105 | 2011 |
| Detecting clinically meaningful shape clusters in medical image data: metrics analysis for hierarchical clustering applied to healthy and pathological aortic arches JL Bruse, MA Zuluaga, A Khushnood, K McLeod, HN Ntsinjana, TY Hsia, ... IEEE Transactions on Biomedical Engineering 64 (10), 2373-2383, 2017 | 100 | 2017 |
| Slic-Seg: A minimally interactive segmentation of the placenta from sparse and motion-corrupted fetal MRI in multiple views G Wang, MA Zuluaga, R Pratt, M Aertsen, T Doel, M Klusmann, AL David, ... Medical image analysis 34, 137-147, 2016 | 93 | 2016 |
| Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection? J Audibert, P Michiardi, F Guyard, S Marti, MA Zuluaga Pattern Recognition 132, 108945, 2022 | 73 | 2022 |
| Matrix profile XXIV: scaling time series anomaly detection to trillions of datapoints and ultra-fast arriving data streams Y Lu, R Wu, A Mueen, MA Zuluaga, E Keogh Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 57 | 2022 |
| Deep learning segmentation of the right ventricle in cardiac MRI: the M&Ms challenge C Martín-Isla, VM Campello, C Izquierdo, K Kushibar, C Sendra-Balcells, ... IEEE Journal of Biomedical and Health Informatics 27 (7), 3302-3313, 2023 | 52 | 2023 |
| Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment R Sparks, G Zombori, R Rodionov, M Nowell, SB Vos, MA Zuluaga, ... International journal of computer assisted radiology and surgery 12, 123-136, 2017 | 52 | 2017 |
| Automatic detection of abnormal vascular cross-sections based on density level detection and support vector machines MA Zuluaga, IE Magnin, M Hernández Hoyos, EJF Delgado Leyton, ... International journal of computer assisted radiology and surgery 6, 163-174, 2011 | 49 | 2011 |
| Micro-CT and histological investigation of the spatial pattern of feto-placental vascular density R Aughwane, C Schaaf, JC Hutchinson, A Virasami, MA Zuluaga, ... Placenta 88, 36-43, 2019 | 46 | 2019 |
| Learning from only positive and unlabeled data to detect lesions in vascular CT images MA Zuluaga, D Hush, EJF Delgado Leyton, MH Hoyos, M Orkisz Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011 | 46 | 2011 |
| Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part I AL Martel, P Abolmaesumi, D Stoyanov, D Mateus, MA Zuluaga, SK Zhou, ... Springer Nature, 2020 | 45 | 2020 |
| Multi-task deep learning for glaucoma detection from color fundus images L Pascal, OJ Perdomo, X Bost, B Huet, S Otálora, MA Zuluaga Scientific Reports 12 (1), 12361, 2022 | 40 | 2022 |
| Selection bias in the reported performances of AD classification pipelines AF Mendelson, MA Zuluaga, M Lorenzi, BF Hutton, S Ourselin, ... NeuroImage: Clinical 14, 400-416, 2017 | 39 | 2017 |
Sebastien OurselinProfessor of Healthcare Engineering, King's College LondonПотвърден имейл адрес: kcl.ac.uk