Hákon Guðbjartsson
- Computational Mathematics top 2%
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- Advanced Neuroimaging Techniques and Applications 9
- Advanced MRI Techniques and Applications 8
- MRI in cancer diagnosis 4
- Aging top 5%
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- Image and Signal Denoising Methods 1
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- NMR spectroscopy and applications 3
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- Functional Brain Connectivity Studies 2
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- Gene expression and cancer classification 2
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- Moyamoya disease diagnosis and treatment 1
- Co-authors
- Samuel PatzRobert V. MulkernFerenc JoleszRichard B. SchwartzFerenc A. JóleszStephan E. MaierSharon PeledKāri Stefánsson
- Partner nations
- United StatesIcelandAustria
In The Last Decade
Hákon Guðbjartsson
16 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Computational Mathematics 66
- Radiology, Nuclear Medicine and Imaging 2.6k
- Aging 77
- Orthopedics and Sports Medicine 311
- Computer Vision and Pattern Recognition 454
Countries citing papers authored by Hákon Guðbjartsson
This map shows the geographic impact of Hákon Guðbjartsson'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 Hákon Guðbjartsson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hákon Guðbjartsson more than expected).
Fields of papers citing papers by Hákon Guðbjartsson
This network shows the impact of papers produced by Hákon Guðbjartsson. 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 Hákon Guðbjartsson. The network helps show where Hákon Guðbjartsson may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hákon Guðbjartsson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 10 | |
| 2 | 2001 | 54 | |
| 3 | 2000 | 89 | |
| 4 | 2000 | 80 | |
| 5 | 2000 | 174 | |
| 6 | 1999 | 305 | |
| 7 | 1999 | 37 | |
| 8 | 1998 | 318 | |
| 9 | 1998 | 146 | |
| 10 | 1998 | 99 | |
| 11 | Diffusion-weighted MR imaging in hypertensive encephalopathy: clues to pathogenesis. | 1998 | 244 |
| 12 | 1997 | 14 | |
| 13 | 1996 | 197 | |
| 14 | The rician distribution of noisy mri databreakdown → | 1995 | 1872 |
| 15 | 1995 | 31 | |
| 16 | 1995 | 18 |
About Hákon Guðbjartsson
Hákon Guðbjartsson is a scholar working on Aging, Radiology, Nuclear Medicine and Imaging and Nuclear and High Energy Physics, having authored 16 papers that have together received 3.7k indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (9 papers), Advanced MRI Techniques and Applications (8 papers), MRI in cancer diagnosis (4 papers), NMR spectroscopy and applications (3 papers), Functional Brain Connectivity Studies (2 papers), Gene expression and cancer classification (2 papers), Moyamoya disease diagnosis and treatment (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Computational Mathematics (66 citations), Radiology, Nuclear Medicine and Imaging (2.6k citations) and Aging (77 citations). Hákon Guðbjartsson has collaborated with scholars based in United States, Iceland and Austria. Frequent co-authors include Samuel Patz, Robert V. Mulkern, Ferenc Jolesz, Richard B. Schwartz, Ferenc A. Jólesz, Stephan E. Maier, Sharon Peled, Kāri Stefánsson, Jeffrey R. Gulcher and I Mórocz. Their work appears in journals such as Bioinformatics, Brain Research and Genome Research.
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.