J.-P. Thirion
- Computer Vision and Pattern Recognition top 0.5%
- Radiology, Nuclear Medicine and Imaging top 1%
- Biomedical Engineering top 10%
- Radiation top 2%
- Artificial Intelligence top 10%
- Co-authors
- Frederik MaesDirk VandermeulenBenoît M. DawantSteven L. HartmannPhilippe DemaerelGérard SubsolS. PrimaNicholas Roberts
- Topics
- Medical Image Segmentation Techniques (11 papers)Advanced Vision and Imaging (5 papers)Medical Imaging Techniques and Applications (3 papers)
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
J.-P. Thirion
14 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Computer Vision and Pattern Recognition 1.2k
- Radiology, Nuclear Medicine and Imaging 1.1k
- Biomedical Engineering 433
- Radiation 313
- Artificial Intelligence 163
Countries citing papers authored by J.-P. Thirion
This map shows the geographic impact of J.-P. Thirion'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 J.-P. Thirion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.-P. Thirion more than expected).
Fields of papers citing papers by J.-P. Thirion
This network shows the impact of papers produced by J.-P. Thirion. 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 J.-P. Thirion. The network helps show where J.-P. Thirion may publish in the future.
Co-authorship network of co-authors of J.-P. Thirion
This figure shows the co-authorship network connecting the top 25 collaborators of J.-P. Thirion. A scholar is included among the top collaborators of J.-P. Thirion based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with J.-P. Thirion. J.-P. Thirion is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 5 | |
| 4 | 7 | |
| 5 | 4 | |
| 6 | 7 | |
| 7 | 49 | |
| 8 | 5 | |
| 9 | 81 | |
| 10 | 170 | |
| 11 | Image matching as a diffusion process: an analogy with Maxwell's demonsbreakdown → | 1656 |
| 12 | 115 | |
| 13 | 8 | |
| 14 | 14 |
About J.-P. Thirion
J.-P. Thirion is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Biophysics, having authored 14 papers that have together received 2.1k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (11 papers), Advanced Vision and Imaging (5 papers) and Medical Imaging Techniques and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Radiology, Nuclear Medicine and Imaging (1.1k citations) and Radiation (313 citations). J.-P. Thirion has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Frederik Maes, Dirk Vandermeulen, Benoît M. Dawant, Steven L. Hartmann, Philippe Demaerel, Gérard Subsol, S. Prima, Nicholas Roberts, Xavier Pennec and Neil Roberts. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis and Nuclear Medicine Communications.
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.