| 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 | 263 | 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 | 177 | 2018 |
| Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning A Hering, L Hansen, TCW Mok, ACS Chung, H Siebert, S Häger, A Lange, ... IEEE Transactions on Medical Imaging 42 (3), 697-712, 2022 | 162 | 2022 |
| 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 | 90 | 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 | 69 | 2022 |
| 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 | 65 | 2019 |
| 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 | 56 | 2018 |
| 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 | 54 | 2020 |
| 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 | 51 | 2019 |
| Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image Segmentation S Vesal, M Gu, R Kosti, A Maier, N Ravikumar IEEE Transactions on Medical Imaging, 1 - 1, 2021 | 41 | 2021 |
| An effective and fast hybrid framework for color image retrieval E Walia, S Vesal, A Pal Sensing and Imaging 15, 1-23, 2014 | 34 | 2014 |
| Fully Automated 3D Cardiac MRI Localisation and Segmentation Using Deep Neural Networks S Vesal, N Ravikumar, A Maier Journal of Imaging 6 (7), 65, 2020 | 33 | 2020 |
| A review of artificial intelligence in prostate cancer detection on imaging I Bhattacharya, YS Khandwala, S Vesal, W Shao, Q Yang, ... Therapeutic advances in urology 14, 17562872221128791, 2022 | 31 | 2022 |
| Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation S Vesal, N Ravikumar, A Maier International Workshop on Statistical Atlases and Computational Models of …, 2020 | 27 | 2020 |
| Age Estimation on Panoramic Dental X-ray Images using Deep Learning S Wallraff, S Vesal, C Syben, R Lutz, A Maier Bildverarbeitung für die Medizin 2021: Proceedings, German Workshop on …, 2021 | 26 | 2021 |
| Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses S Ellmann, E Wenkel, M Dietzel, C Bielowski, S Vesal, A Maier, ... Plos one 15 (1), e0228446, 2020 | 25 | 2020 |
| Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study S Vesal, I Gayo, I Bhattacharya, S Natarajan, LS Marks, DC Barratt, ... Medical image analysis 82, 102620, 2022 | 21 | 2022 |
| Deep learning-based denoising of mammographic images using physics-driven data augmentation D Eckert, S Vesal, L Ritschl, S Kappler, A Maier Bildverarbeitung für die Medizin 2020: Algorithmen–Systeme–Anwendungen …, 2020 | 21 | 2020 |
| Dilated deeply supervised networks for hippocampus segmentation in MRI L Folle, S Vesal, N Ravikumar, A Maier Bildverarbeitung für die Medizin 2019: Algorithmen–Systeme–Anwendungen …, 2019 | 20 | 2019 |
| COPD Classification in CT Images Using a 3D Convolutional Neural Network J Ahmed, S Vesal, F Durlak, R Kaergel, N Ravikumar, M Rémy-Jardin, ... Bildverarbeitung für die Medizin 2020, 2020 | 19 | 2020 |
Andreas K. MaierUniversity of Erlangen-NurembergVerified email at fau.de
