PA Cook
Impact in
- Computational Mathematics top 10%
- Tensor decomposition and applications
-
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- MRI in cancer diagnosis
Papers in
-
- Advanced Neuroimaging Techniques and Applications 6
- Advanced MRI Techniques and Applications 5
- MRI in cancer diagnosis 2
-
- Fetal and Pediatric Neurological Disorders 1
- Co-authors
- Daniel C. Alexander (6 shared papers)KK Seunarine (4 shared papers)MG Hall (2 shared papers)Shahrum Nedjati-Gilani (4 shared papers)Yu Bai (2 shared papers)Geoff J.M. Parker (2 shared papers)
- Journals
- UCL Discovery (University College London) (5 papers)
- Partner nations
- Australia
In The Last Decade
PA Cook
6 papers receiving 382 citations
Peers
Comparison fields: 5 of 53
- Computational Mathematics 13
- Radiology, Nuclear Medicine and Imaging 311
- Orthopedics and Sports Medicine 52
- Cognitive Neuroscience 98
- Pediatrics, Perinatology and Child Health 58
Countries citing papers authored by PA Cook
This map shows the geographic impact of PA Cook'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 PA Cook with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites PA Cook more than expected).
Fields of papers citing papers by PA Cook
This network shows the impact of papers produced by PA Cook. 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 PA Cook. The network helps show where PA Cook may publish in the future.
Co-authors
The 6 scholars most cited alongside PA Cook, 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 | Camino: Open-Source Diffusion-MRI Reconstruction and Processing | 2006 | 370 |
| 2 | Tractography with multiple fibre directions | 2003 | 6 |
| 3 | 2005 | 4 | |
| 4 | A general framework for multiple-fibre PICo tractography | 2006 | 3 |
| 5 | Voxel-Based Classification of White Matter Fibre Complexity in Diffusion MRI | 2005 | 1 |
| 6 | Exploiting the fibre-orientation distribution for probabilistic tractography | 2008 | 1 |
About PA Cook
PA Cook is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Cognitive Neuroscience, Nuclear and High Energy Physics and Infectious Diseases, having authored 6 papers that have together received 385 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (6 papers), Advanced MRI Techniques and Applications (5 papers), MRI in cancer diagnosis (2 papers), Fetal and Pediatric Neurological Disorders (1 paper), Functional Brain Connectivity Studies (1 paper) and NMR spectroscopy and applications (1 paper). The work is most often cited by research in Computational Mathematics (13 citations), Radiology, Nuclear Medicine and Imaging (311 citations), Orthopedics and Sports Medicine (52 citations), Cognitive Neuroscience (98 citations) and Pediatrics, Perinatology and Child Health (58 citations). PA Cook has collaborated with scholars based in Australia. Frequent co-authors include Daniel C. Alexander, KK Seunarine, MG Hall, Shahrum Nedjati-Gilani, Yu Bai and Geoff J.M. Parker. Their work appears in journals such as UCL Discovery (University College London).
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.