Daniel Rueckert
Impact in
- Radiology, Nuclear Medicine and Imaging top 0.01%
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Computer Vision and Pattern Recognition top 0.01%
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Advanced Image Processing Techniques
Papers in
-
- Advanced MRI Techniques and Applications 123
- Advanced Neuroimaging Techniques and Applications 74
- Medical Imaging Techniques and Applications 70
- Radiomics and Machine Learning in Medical Imaging 48
-
- Medical Image Segmentation Techniques 190
- Co-authors
- Joseph V. Hajnal (121 shared papers)David J. Hawkes (15 shared papers)José Caballero (9 shared papers)Paul Aljabar (67 shared papers)David Hill (30 shared papers)Ben Glocker (34 shared papers)Wenzhe Shi (35 shared papers)Alexander Hammers (40 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (58 papers)NeuroImage (45 papers)Medical Image Analysis (37 papers)PLoS ONE (11 papers)Journal of Cardiovascular Magnetic Resonance (10 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Daniel Rueckert
570 papers receiving 44.7k citations
Daniel Rueckert's Hit Papers
Peers
Comparison fields: 5 of 214
- Radiology, Nuclear Medicine and Imaging 17.0k
- Computer Vision and Pattern Recognition 15.6k
- Health Informatics 653
- Neurology 3.7k
- Media Technology 2.7k
Countries citing papers authored by Daniel Rueckert
This map shows the geographic impact of Daniel Rueckert's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Rueckert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Rueckert more than expected).
Fields of papers citing papers by Daniel Rueckert
This network shows the impact of papers produced by Daniel Rueckert. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Rueckert. The network helps show where Daniel Rueckert may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Rueckert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 597 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data Hit paper breakdown → | 2006 | 5330 |
| 2 | Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Hit paper breakdown → | 2016 | 4416 |
| 3 | Nonrigid registration using free-form deformations: application to breast MR images Hit paper breakdown → | 1999 | 3764 |
| 4 | Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation Hit paper breakdown → | 2016 | 2175 |
| 5 | Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration Hit paper breakdown → | 2009 | 1680 |
| 6 | Medical Image Computing and Computer-Assisted Intervention Hit paper breakdown → | 2009 | 1290 |
| 7 | Attention gated networks: Learning to leverage salient regions in medical images Hit paper breakdown → | 2019 | 1289 |
| 8 | A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction Hit paper breakdown → | 2017 | 828 |
| 9 | Automatic anatomical brain MRI segmentation combining label propagation and decision fusion Hit paper breakdown → | 2006 | 671 |
| 10 | Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy Hit paper breakdown → | 2009 | 666 |
| 11 | Acquisition and voxelwise analysis of multi-subject diffusion data with Tract-Based Spatial Statistics Hit paper breakdown → | 2007 | 492 |
| 12 | Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease Hit paper breakdown → | 2018 | 461 |
| 13 | Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation Hit paper breakdown → | 2017 | 448 |
| 14 | Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction Hit paper breakdown → | 2018 | 392 |
| 15 | Self-supervised learning for medical image analysis using image context restoration Hit paper breakdown → | 2019 | 350 |
| 16 | 2012 | 334 | |
| 17 | 2009 | 302 | |
| 18 | 2003 | 297 | |
| 19 | End-to-end privacy preserving deep learning on multi-institutional medical imaging Hit paper breakdown → | 2021 | 270 |
| 20 | 2007 | 264 |
About Daniel Rueckert
Daniel Rueckert is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Pediatrics, Perinatology and Child Health and Biomedical Engineering, having authored 597 papers that have together received 45.5k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (190 papers), Advanced MRI Techniques and Applications (123 papers), Advanced Neuroimaging Techniques and Applications (74 papers), Medical Imaging Techniques and Applications (70 papers), Neonatal and fetal brain pathology (48 papers), Radiomics and Machine Learning in Medical Imaging (48 papers), Functional Brain Connectivity Studies (46 papers) and Fetal and Pediatric Neurological Disorders (45 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (17.0k citations), Computer Vision and Pattern Recognition (15.6k citations), Health Informatics (653 citations), Neurology (3.7k citations) and Media Technology (2.7k citations). Daniel Rueckert has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Joseph V. Hajnal, David J. Hawkes, José Caballero, Paul Aljabar, David Hill, Ben Glocker, Wenzhe Shi, Alexander Hammers, Mark Jenkinson and Luke Sonoda. Their work appears in journals such as IEEE Transactions on Medical Imaging, NeuroImage, Medical Image Analysis, PLoS ONE and Journal of Cardiovascular Magnetic Resonance.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.