Kumar Rajamani
Impact in
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- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
- Neurology top 10%
- Brain Tumor Detection and Classification
Papers in
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- Medical Image Segmentation Techniques 13
- Digital Imaging for Blood Diseases 6
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- Retinal Imaging and Analysis 8
- COVID-19 diagnosis using AI 6
- Co-authors
- Martin Styner (11 shared papers)Lutz‐Peter Nolte (3 shared papers)Chris Taylor (1 shared paper)Rhodri Davies (1 shared paper)Gábor Székely (1 shared paper)Miguel Á. González Ballester (7 shared papers)V. L. Lajish (5 shared papers)Guoyan Zheng (3 shared papers)
- Journals
- Journal of the Neurological Sciences (3 papers)Computer Aided Surgery (2 papers)Multimedia Tools and Applications (2 papers)New England Journal of Medicine (2 papers)Journal of Stroke and Cerebrovascular Diseases (2 papers)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Kumar Rajamani
60 papers receiving 854 citations
Peers
Comparison fields: 5 of 97
- Computer Vision and Pattern Recognition 349
- Neurology 71
- Internal Medicine 24
- Geometry and Topology 62
- Computational Mechanics 142
Countries citing papers authored by Kumar Rajamani
This map shows the geographic impact of Kumar Rajamani'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 Kumar Rajamani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Rajamani more than expected).
Fields of papers citing papers by Kumar Rajamani
This network shows the impact of papers produced by Kumar Rajamani. 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 Kumar Rajamani. The network helps show where Kumar Rajamani may publish in the future.
Co-authors
The 25 scholars most cited alongside Kumar Rajamani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 212 | |
| 2 | 2007 | 88 | |
| 3 | 2000 | 57 | |
| 4 | 2011 | 41 | |
| 5 | 2007 | 40 | |
| 6 | 2022 | 35 | |
| 7 | 2021 | 35 | |
| 8 | 2016 | 33 | |
| 9 | 2017 | 26 | |
| 10 | 2005 | 23 | |
| 11 | 2015 | 22 | |
| 12 | 2011 | 20 | |
| 13 | 2021 | 19 | |
| 14 | 2004 | 18 | |
| 15 | 2012 | 16 | |
| 16 | 2005 | 14 | |
| 17 | 2015 | 12 | |
| 18 | 2005 | 12 | |
| 19 | 2016 | 12 | |
| 20 | 2016 | 12 |
About Kumar Rajamani
Kumar Rajamani is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Computational Mechanics, Artificial Intelligence and Biomedical Engineering, having authored 63 papers that have together received 905 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (13 papers), Retinal Imaging and Analysis (8 papers), Medical Imaging and Analysis (8 papers), 3D Shape Modeling and Analysis (8 papers), Digital Imaging for Blood Diseases (6 papers), AI in cancer detection (6 papers), COVID-19 diagnosis using AI (6 papers) and Brain Tumor Detection and Classification (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (349 citations), Neurology (71 citations), Internal Medicine (24 citations), Geometry and Topology (62 citations) and Computational Mechanics (142 citations). Kumar Rajamani has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Martin Styner, Lutz‐Peter Nolte, Chris Taylor, Rhodri Davies, Gábor Székely, Miguel Á. González Ballester, V. L. Lajish, Guoyan Zheng, Lutz P. Nolte and Mattias P. Heinrich. Their work appears in journals such as Journal of the Neurological Sciences, Computer Aided Surgery, Multimedia Tools and Applications, New England Journal of Medicine and Journal of Stroke and Cerebrovascular Diseases.
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.