Martin Rajchl
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 2%
- Cardiology and Cardiovascular Medicine top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering top 10%
- Co-authors
- Daniel RueckertEranga UkwattaJames A. WhiteBen GlockerWu QiuTerry M. PetersAaron FensterEnzo Ferrante
- Topics
- Medical Image Segmentation Techniques (33 papers)Advanced Neural Network Applications (15 papers)Cardiac Valve Diseases and Treatments (10 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingHealth Informatics
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Martin Rajchl
60 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 110
- Radiology, Nuclear Medicine and Imaging 640
- Computer Vision and Pattern Recognition 584
- Cardiology and Cardiovascular Medicine 311
- Artificial Intelligence 285
- Biomedical Engineering 264
Countries citing papers authored by Martin Rajchl
This map shows the geographic impact of Martin Rajchl'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 Martin Rajchl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Rajchl more than expected).
Fields of papers citing papers by Martin Rajchl
This network shows the impact of papers produced by Martin Rajchl. 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 Martin Rajchl. The network helps show where Martin Rajchl may publish in the future.
Co-authorship network of co-authors of Martin Rajchl
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Rajchl. A scholar is included among the top collaborators of Martin Rajchl 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 Martin Rajchl. Martin Rajchl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 252 | |
| 3 | 8 | |
| 4 | 6 | |
| 5 | 15 | |
| 6 | 29 | |
| 7 | 27 | |
| 8 | 10 | |
| 9 | 39 | |
| 10 | 22 | |
| 11 | 21 | |
| 12 | 83 | |
| 13 | 40 | |
| 14 | 11 | |
| 15 | 3 | |
| 16 | 46 | |
| 17 | 19 | |
| 18 | 36 | |
| 19 | 4 | |
| 20 | 14 |
About Martin Rajchl
Martin Rajchl is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine, having authored 61 papers that have together received 1.6k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (33 papers), Advanced Neural Network Applications (15 papers) and Cardiac Valve Diseases and Treatments (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (584 citations), Radiology, Nuclear Medicine and Imaging (640 citations) and Health Informatics (24 citations). Martin Rajchl has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Daniel Rueckert, Eranga Ukwatta, James A. White, Ben Glocker, Wu Qiu, Terry M. Peters, Aaron Fenster, Enzo Ferrante, Sarah Parisot and Sofia Ira Ktena. Their work appears in journals such as Circulation, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.
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.