Petru-Daniel Tudosiu
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Neurology
- Biomedical Engineering
- Co-authors
- M. Jorge CardosoWalter Hugo Lopez PinayaSébastien OurselinParashkev NachevGeraint ReesRobert GrayMark S. GrahamAshay Patel
- Topics
- Generative Adversarial Networks and Image Synthesis (4 papers)Anomaly Detection Techniques and Applications (4 papers)COVID-19 diagnosis using AI (3 papers)
- Partner nations
- United KingdomUnited StatesSweden
In The Last Decade
Petru-Daniel Tudosiu
11 papers receiving 180 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 93
- Radiology, Nuclear Medicine and Imaging 73
- Computer Vision and Pattern Recognition 72
- Neurology 40
- Biomedical Engineering 12
Countries citing papers authored by Petru-Daniel Tudosiu
This map shows the geographic impact of Petru-Daniel Tudosiu'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 Petru-Daniel Tudosiu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Petru-Daniel Tudosiu more than expected).
Fields of papers citing papers by Petru-Daniel Tudosiu
This network shows the impact of papers produced by Petru-Daniel Tudosiu. 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 Petru-Daniel Tudosiu. The network helps show where Petru-Daniel Tudosiu may publish in the future.
Co-authorship network of co-authors of Petru-Daniel Tudosiu
This figure shows the co-authorship network connecting the top 25 collaborators of Petru-Daniel Tudosiu. A scholar is included among the top collaborators of Petru-Daniel Tudosiu 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 Petru-Daniel Tudosiu. Petru-Daniel Tudosiu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 12 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 33 | |
| 8 | 4 | |
| 9 | 17 | |
| 10 | 9 | |
| 11 | 99 |
About Petru-Daniel Tudosiu
Petru-Daniel Tudosiu is a scholar working on Biophysics, Artificial Intelligence and Geriatrics and Gerontology, having authored 11 papers that have together received 187 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (4 papers), Anomaly Detection Techniques and Applications (4 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Neurology (40 citations), Computer Vision and Pattern Recognition (72 citations) and Radiology, Nuclear Medicine and Imaging (73 citations). Petru-Daniel Tudosiu has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include M. Jorge Cardoso, Walter Hugo Lopez Pinaya, Sébastien Ourselin, Parashkev Nachev, Geraint Rees, Robert Gray, Mark S. Graham, Ashay Patel, Matthew F. Glasser and Logan Z. J. Williams. Their work appears in journals such as IEEE Transactions on Medical Imaging, BMC Medicine and Medical Image Analysis.
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.