| Bi-directional ConvLSTM U-Net with densley connected convolutions R Azad, M Asadi-Aghbolaghi, M Fathy, S Escalera Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 536 | 2019 |
| Diffusion models in medical imaging: A comprehensive survey A Kazerouni, EK Aghdam, M Heidari, R Azad, M Fayyaz, I Hacihaliloglu, ... Medical Image Analysis, 102846, 2023 | 465* | 2023 |
| Hiformer: Hierarchical multi-scale representations using transformers for medical image segmentation M Heidari, A Kazerouni, M Soltany, R Azad, EK Aghdam, J Cohen-Adad, ... Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023 | 301 | 2023 |
| Medical image segmentation review: The success of u-net R Azad, EK Aghdam, A Rauland, Y Jia, AH Avval, A Bozorgpour, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 290 | 2024 |
| Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review R Azad, A Kazerouni, M Heidari, EK Aghdam, A Molaei, Y Jia, A Jose, ... Medical Image Analysis, 2023 | 154 | 2023 |
| Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation R Azad, M Asadi-Aghbolaghi, M Fathy, S Escalera ECCV, European Conference on Computer Vision, 2020 | 147 | 2020 |
| Transdeeplab: Convolution-free transformer-based deeplab v3+ for medical image segmentation R Azad, M Heidari, M Shariatnia, EK Aghdam, S Karimijafarbigloo, E Adeli, ... International Workshop on PRedictive Intelligence In MEdicine, 91-102, 2022 | 137 | 2022 |
| DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation R Azad, R Arimond, EK Aghdam, A Kazerouni, D Merhof MICCAI 2023 workshop, 2022 | 116 | 2022 |
| On the texture bias for few-shot cnn segmentation R Azad, AR Fayjie, C Kauffmann, I Ben Ayed, M Pedersoli, J Dolz Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 101 | 2021 |
| Contextual Attention Network: Transformer Meets U-Net A Reza, H Moein, W Yuli, M Dorit MICCAI 2022, 2022 | 99 | 2022 |
| Semi-supervised few-shot learning for medical image segmentation AR Feyjie, R Azad, M Pedersoli, C Kauffman, IB Ayed, J Dolz arXiv preprint arXiv:2003.08462, 2020 | 97 | 2020 |
| Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation R Azad, L Niggemeier, M Huttemann, A Kazerouni, EK Aghdam, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023 | 95 | 2023 |
| TransNorm: Transformer Provides a Strong Spatial Normalization Mechanism for a Deep Segmentation Model R Azad, MT AL-Antary, M Heidari, D Merhof IEEE Access, 2022 | 86 | 2022 |
| Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation M Asadi-Aghbolaghi, R Azad, M Fathy, S Escalera arXiv:2003.05056, 1-10, 2020 | 83 | 2020 |
| Implicit neural representation in medical imaging: A comparative survey A Molaei, A Aminimehr, A Tavakoli, A Kazerouni, B Azad, R Azad, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 77 | 2023 |
| SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalities R Azad, N Khosravi, D Merhof International Conference on Medical Imaging with Deep Learning, 48-62, 2022 | 76 | 2022 |
| Foundational models in medical imaging: A comprehensive survey and future vision B Azad, R Azad, S Eskandari, A Bozorgpour, A Kazerouni, I Rekik, ... arXiv preprint arXiv:2310.18689, 2023 | 61 | 2023 |
| Medical Image Segmentation on MRI Images with Missing Modalities: A Review R Azad, N Khosravi, M Dehghanmanshadi, J Cohen-Adad, D Merhof Computational Visual Media, 2022 | 61 | 2022 |
| Deep Frequency Re-Calibration U-Net for Medical Image Segmentation R Azad, A Bozorgpour, M Asadi-Aghbolaghi, D Merhof, S Escalera Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 59 | 2021 |
| Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation EK Aghdam, R Azad, M Zarvani, D Merhof ISBI 2023, 2022 | 58 | 2022 |
Dorit MerhofProfessor, Faculty of Informatics and Computer Science, University of RegensburgEmail yang diverifikasi di informatik.uni-regensburg.de