| Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography HA Kirişli, M Schaap, CT Metz, AS Dharampal, WB Meijboom, ... Medical image analysis 17 (8), 859-876, 2013 | 248 | 2013 |
| Automatic segmentation, detection and quantification of coronary artery stenoses on CTA R Shahzad, H Kirişli, C Metz, H Tang, M Schaap, L van Vliet, W Niessen, ... The international journal of cardiovascular imaging 29, 1847-1859, 2013 | 105 | 2013 |
| An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework JM Wolterink, T Leiner, BD De Vos, JL Coatrieux, BM Kelm, S Kondo, ... Medical physics 43 (5), 2361-2373, 2016 | 92 | 2016 |
| Vessel Specific Coronary Artery Calcium Scoring: An Automatic System R Shahzad, T van Walsum, M Schaap, A Rossi, S Klein, AC Weustink, ... Academic Radiology 20 (1), 1-9, 2012 | 90 | 2012 |
| Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer MS Elmahdy, T Jagt, RT Zinkstok, Y Qiao, R Shahzad, H Sokooti, ... Medical physics 46 (8), 3329-3343, 2019 | 69 | 2019 |
| Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach R Shahzad, D Bos, CT Metz, A Rossi, HA Kirisli, A van der Lugt, S Klein, ... Medical Physics 40 (9), 091910, 2013 | 68 | 2013 |
| Epicardial fat volume is related to atherosclerotic calcification in multiple vessel beds D Bos, R Shahzad, T van Walsum, LJ van Vliet, OH Franco, A Hofman, ... European Heart Journal-Cardiovascular Imaging 16 (11), 1264-1269, 2015 | 62 | 2015 |
| Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning R Shahzad, L Pennig, L Goertz, F Thiele, C Kabbasch, M Schlamann, ... Scientific Reports 10 (1), 21799, 2020 | 61 | 2020 |
| Fully automatic segmentation of left atrium and pulmonary veins in late gadolinium‐enhanced MRI: Towards objective atrial scar assessment Q Tao, EG Ipek, R Shahzad, FF Berendsen, S Nazarian, RJ van der Geest Journal of magnetic resonance imaging 44 (2), 346-354, 2016 | 57 | 2016 |
| Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II S Ourselin, L Joskowicz, MR Sabuncu, G Unal, W Wells Springer, 2016 | 53 | 2016 |
| Epicardial fat volume and the risk of atrial fibrillation in the general population free of cardiovascular disease D Bos, MW Vernooij, R Shahzad, M Kavousi, A Hofman, T van Walsum, ... JACC: Cardiovascular Imaging 10 (11), 1405-1407, 2017 | 45 | 2017 |
| Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans R Shahzad, D Bos, RPJ Budde, K Pellikaan, WJ Niessen, A Van Der Lugt, ... Physics in Medicine & Biology 62 (9), 3798, 2017 | 41 | 2017 |
| Fully automated MR detection and segmentation of brain metastases in non‐small cell lung cancer using deep learning ST Jünger, UCI Hoyer, D Schaufler, KR Laukamp, L Goertz, F Thiele, ... Journal of Magnetic Resonance Imaging 54 (5), 1608-1622, 2021 | 38 | 2021 |
| Automated detection and segmentation of brain metastases in malignant melanoma: evaluation of a dedicated deep learning model L Pennig, R Shahzad, L Caldeira, S Lennartz, F Thiele, L Goertz, D Zopfs, ... American Journal of Neuroradiology 42 (4), 655-662, 2021 | 37 | 2021 |
| Fully-automatic left ventricular segmentation from long-axis cardiac cine MR scans R Shahzad, Q Tao, O Dzyubachyk, M Staring, BPF Lelieveldt, ... Medical image analysis 39, 44-55, 2017 | 35 | 2017 |
| Automated agatston score computation in a large dataset of non ECG-gated chest computed tomography G González, GR Washko, RSJ Estépar 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 53-57, 2016 | 35 | 2016 |
| Primary central nervous system lymphoma: clinical evaluation of automated segmentation on multiparametric MRI using deep learning L Pennig, UCI Hoyer, L Goertz, R Shahzad, T Persigehl, F Thiele, ... Journal of Magnetic Resonance Imaging 53 (1), 259-268, 2021 | 27 | 2021 |
| Automatic stenosis detection, quantification and lumen segmentation of the coronary arteries using two-point centerline extraction scheme R Shahzad, T van Walsum, H Kirisli, H Tang, C Metz, M Schaap, ... Proceedings of MICCAI Workshop 3D Cardiovascular Imaging: A MICCAI …, 2012 | 27 | 2012 |
| Learning‐based automated segmentation of the carotid artery vessel wall in dual‐sequence MRI using subdivision surface fitting S Gao, R van ‘t Klooster, PH Kitslaar, BF Coolen, AM van den Berg, ... Medical physics 44 (10), 5244-5259, 2017 | 25 | 2017 |
| Automated Cardiovascular Segmentation in Patients with Congenital Heart Disease from 3D CMR scans: Combining Multi-Atlases and Level-Sets R Shahzad, S Gao, Q Tao, O Dzyubachyk, R van der Geest Reconstruction, Segmentation, and Analysis of Medical Images: First …, 2016 | 25 | 2016 |
Theo van WalsumAssociate Professor in Image Guidance in Interventions and Therapy, Erasmus MCVerified email at erasmusmc.nl
