| A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging Z Xiong, Q Xia, Z Hu, N Huang, C Bian, Y Zheng, S Vesal, N Ravikumar, ... Medical image analysis 67, 101832, 2021 | 169 | 2021 |
| Classification of breast cancer histology images using transfer learning S Vesal, N Ravikumar, AA Davari, S Ellmann, A Maier Image Analysis and Recognition: 15th International Conference, ICIAR 2018 …, 2018 | 154 | 2018 |
| SkinNet: A deep learning framework for skin lesion segmentation S Vesal, N Ravikumar, A Maier 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference …, 2018 | 77 | 2018 |
| Deep learning in medical image registration X Chen, A Diaz-Pinto, N Ravikumar, AF Frangi Progress in Biomedical Engineering 3 (1), 012003, 2021 | 68 | 2021 |
| Subject-specific multi-poroelastic model for exploring the risk factors associated with the early stages of Alzheimer's disease L Guo, JC Vardakis, T Lassila, M Mitolo, N Ravikumar, D Chou, M Lange, ... Interface focus 8 (1), 20170019, 2018 | 55 | 2018 |
| Cardiac segmentation on late gadolinium enhancement MRI: a benchmark study from multi-sequence cardiac MR segmentation challenge X Zhuang, J Xu, X Luo, C Chen, C Ouyang, D Rueckert, VM Campello, ... Medical Image Analysis 81, 102528, 2022 | 54 | 2022 |
| A multi-task framework for skin lesion detection and segmentation S Vesal, S Malakarjun Patil, N Ravikumar, AK Maier International Workshop on Computer-Assisted and Robotic Endoscopy, 285-293, 2018 | 54 | 2018 |
| Mitosis domain generalization in histopathology images—the MIDOG challenge M Aubreville, N Stathonikos, CA Bertram, R Klopfleisch, N Ter Hoeve, ... Medical Image Analysis 84, 102699, 2023 | 53 | 2023 |
| Dilated convolutions in neural networks for left atrial segmentation in 3D gadolinium enhanced-MRI S Vesal, N Ravikumar, A Maier Statistical Atlases and Computational Models of the Heart. Atrial …, 2019 | 49 | 2019 |
| A constitutive model for ballistic gelatin at surgical strain rates N Ravikumar, C Noble, E Cramphorn, ZA Taylor Journal of the mechanical behavior of biomedical materials 47, 87-94, 2015 | 45 | 2015 |
| Group-wise similarity registration of point sets using Student’s t-mixture model for statistical shape models N Ravikumar, A Gooya, S Çimen, AF Frangi, ZA Taylor Medical image analysis 44, 156-176, 2018 | 43 | 2018 |
| A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT S Vesal, N Ravikumar, A Maier arXiv preprint arXiv:1905.07710, 2019 | 42 | 2019 |
| The effect of data augmentation on classification of atrial fibrillation in short single-lead ECG signals using deep neural networks FN Hatamian, N Ravikumar, S Vesal, FP Kemeth, M Struck, A Maier ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 41 | 2020 |
| Frangi-net W Fu, K Breininger, R Schaffert, N Ravikumar, T Würfl, J Fujimoto, E Moult, ... Bildverarbeitung für die Medizin 2018: Algorithmen-Systeme-Anwendungen …, 2018 | 41 | 2018 |
| Generalised coherent point drift for group-wise registration of multi-dimensional point sets N Ravikumar, A Gooya, AF Frangi, ZA Taylor Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 37 | 2017 |
| Super-resolution of cardiac MR cine imaging using conditional GANs and unsupervised transfer learning Y Xia, N Ravikumar, JP Greenwood, S Neubauer, SE Petersen, AF Frangi Medical Image Analysis 71, 102037, 2021 | 36 | 2021 |
| Predicting myocardial infarction through retinal scans and minimal personal information A Diaz-Pinto, N Ravikumar, R Attar, A Suinesiaputra, Y Zhao, E Levelt, ... Nature Machine Intelligence 4 (1), 55-61, 2022 | 35 | 2022 |
| Federated simulation for medical imaging D Li, A Kar, N Ravikumar, AF Frangi, S Fidler Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 30 | 2020 |
| Magnetic resonance elastography of the brain: an in silico study to determine the influence of cranial anatomy DM McGrath, N Ravikumar, ID Wilkinson, AF Frangi, ZA Taylor Magnetic resonance in medicine 76 (2), 645-662, 2016 | 29 | 2016 |
| Adapt everywhere: unsupervised adaptation of point-clouds and entropy minimization for multi-modal cardiac image segmentation S Vesal, M Gu, R Kosti, A Maier, N Ravikumar IEEE Transactions on Medical Imaging 40 (7), 1838-1851, 2021 | 27 | 2021 |
Andreas K. MaierUniversity of Erlangen-NurembergVerified email at fau.de
