| Fast volume reconstruction from motion corrupted stacks of 2D slices B Kainz, M Steinberger, W Wein, M Kuklisova-Murgasova, ... IEEE transactions on medical imaging 34 (9), 1901-1913, 2015 | 207 | 2015 |
| Standardized evaluation system for left ventricular segmentation algorithms in 3D echocardiography O Bernard, JG Bosch, B Heyde, M Alessandrini, D Barbosa, ... IEEE transactions on medical imaging 35 (4), 967-977, 2015 | 113 | 2015 |
| Automated fetal brain segmentation from 2D MRI slices for motion correction K Keraudren, M Kuklisova-Murgasova, V Kyriakopoulou, C Malamateniou, ... NeuroImage 101, 633-643, 2014 | 109 | 2014 |
| Fast fully automatic brain detection in fetal MRI using dense rotation invariant image descriptors B Kainz, K Keraudren, V Kyriakopoulou, M Rutherford, JV Hajnal, ... 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 1230-1233, 2014 | 49 | 2014 |
| Localisation of the brain in fetal MRI using bundled SIFT features K Keraudren, V Kyriakopoulou, M Rutherford, JV Hajnal, D Rueckert Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 37 | 2013 |
| Motion corrected 3D reconstruction of the fetal thorax from prenatal MRI B Kainz, C Malamateniou, M Murgasova, K Keraudren, M Rutherford, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 30 | 2014 |
| Learning Shape Representations for Multi-Atlas Endocardium Segmentation in 3D Echo Images O Oktay, W Shi, K Keraudren, J Caballero, D Rueckert | 24 | 2014 |
| Automated Localization of Fetal Organs in MRI Using Random Forests with Steerable Features K Keraudren, B Kainz, O Oktay, V Kyriakopoulou, M Rutherford, JV Hajnal, ... | 23 | 2015 |
| Structured decision forests for multi-modal ultrasound image registration O Oktay, A Schuh, M Rajchl, K Keraudren, A Gomez, MP Heinrich, ... Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 22 | 2015 |
| Automatic brain localization in fetal MRI using superpixel graphs A Alansary, M Lee, K Keraudren, B Kainz, C Malamateniou, M Rutherford, ... Machine Learning Meets Medical Imaging: First International Workshop, MLMMI …, 2015 | 20 | 2015 |
| Flexible reconstruction and correction of unpredictable motion from stacks of 2D images B Kainz, A Alansary, C Malamateniou, K Keraudren, M Rutherford, ... Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 18 | 2015 |
| Endocardial 3D Ultrasound Segmentation using Autocontext Random Forests K Keraudren, O Oktay, W Shi, JV Hajnal, D Rueckert | 18 | 2014 |
| Probabilistic edge map (PEM) for 3D ultrasound image registration and multi-atlas left ventricle segmentation O Oktay, A Gomez, K Keraudren, A Schuh, W Bai, W Shi, G Penney, ... Functional Imaging and Modeling of the Heart: 8th International Conference …, 2015 | 14 | 2015 |
| Methods for monitoring compositional changes in a body ID Diener, M Foster, D Greer, K Keraudren, B Whitcher US Patent App. 15/419,983, 2018 | 4 | 2018 |
| Two-Step Watershed Segmentation of Epithelial Cells K Keraudren, M Spitaler, VMM Braga, D Rueckert, L Pizarro | 4 | 2011 |
| Adaptive scan strategies for fetal MRI imaging using slice to volume techniques B Kainz, C Malamateniou, G Ferrazzi, M Murgasova, J Egger, ... 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 849-852, 2015 | 3 | 2015 |
| Sparsity based spectral embedding: Application to multi-atlas echocardiography segmentation O Oktay, W Shi, J Caballero, K Keraudren, D Rueckert Proceedings of MICCAI STMI Workshop 186, 2014 | 3 | 2014 |
| Methods for predicting compositional body changes ID Diener, M Foster, D Greer, K Keraudren, B Whitcher US Patent App. 15/419,998, 2018 | 2 | 2018 |
| Patient motion tracking system configured for automatic ROI generation K Keraudren US Patent US20200402245A1, 2020 | | 2020 |
| Methods for processing three dimensional body images ID DIENER, M Foster, D Greer, K KERAUDREN, B WHITCHER WO Patent WO2018132090A1, 2018 | | 2018 |
Daniel RueckertTechnical University of Munich and Imperial College LondonПотвърден имейл адрес: tum.de
