Standout Papers
- Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data (2006)
- Nonrigid registration using free-form deformations: application to breast MR images (1999)
- Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation (2016)
- Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration (2009)
- Medical Image Computing and Computer-Assisted Intervention (2009)
- Attention gated networks: Learning to leverage salient regions in medical images (2019)
- A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction (2017)
- Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy (2009)
- Automatic anatomical brain MRI segmentation combining label propagation and decision fusion (2006)
- Acquisition and voxelwise analysis of multi-subject diffusion data with Tract-Based Spatial Statistics (2007)
- Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease (2018)
- Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation (2017)
- Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction (2018)
- Self-supervised learning for medical image analysis using image context restoration (2019)
- End-to-end privacy preserving deep learning on multi-institutional medical imaging (2021)
- Evaluation and mitigation of the limitations of large language models in clinical decision-making (2024)
Immediate Impact
1 by Nobel laureates 19 from Science/Nature 110 standout
Citing Papers
Alzheimer’s Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
2024 Standout
Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association
2024 Standout
Works of Daniel Rueckert being referenced
Cardiac Rhythm Device Identification Using Neural Networks
2019
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease
2018 Standout
Author Peers
| Author | Last Decade | Papers | Cites | ||||
|---|---|---|---|---|---|---|---|
| Daniel Rueckert | 18388 | 10346 | 5064 | 6327 | 478 | 35.9k | |
| Ron Kikinis | 13668 | 5329 | 3232 | 7057 | 331 | 32.6k | |
| Dinggang Shen | 18922 | 13777 | 4236 | 12267 | 1.2k | 47.2k | |
| James C. Gee | 13312 | 4393 | 2990 | 8972 | 308 | 30.0k | |
| Christos Davatzikos | 11834 | 6433 | 1640 | 10431 | 583 | 31.3k | |
| D. Louis Collins | 12982 | 6325 | 2387 | 11154 | 489 | 34.2k | |
| Sébastien Ourselin | 9295 | 4267 | 1634 | 3566 | 727 | 24.2k | |
| Ferenc A. Jólesz | 20109 | 3535 | 3292 | 7119 | 432 | 42.2k | |
| Max A. Viergever | 15990 | 10955 | 1171 | 2183 | 524 | 31.3k | |
| Guido Gerig | 8129 | 4156 | 3325 | 5071 | 235 | 20.5k | |
| Arthur W. Toga | 18219 | 4087 | 5184 | 28732 | 755 | 66.2k |
All Works
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