Abhirup Banerjee
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Cardiology and Cardiovascular Medicine
- Infectious Diseases
- Co-authors
- Pradipta MajiVicente GrauMarcel BeetzSurajit RayLouise S. MackenzieMichail MamalakisBart VorselaarsMark Baker
- Topics
- Medical Image Segmentation Techniques (17 papers)3D Shape Modeling and Analysis (8 papers)Cardiac Imaging and Diagnostics (7 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- Scientific ReportsInternational Journal of Molecular SciencesIEEE Transactions on Image Processing
- Partner nations
- United KingdomIndiaAustralia
In The Last Decade
Abhirup Banerjee
44 papers receiving 463 citations
Peers
Comparison fields: 5 of 82
- Radiology, Nuclear Medicine and Imaging 208
- Computer Vision and Pattern Recognition 139
- Artificial Intelligence 110
- Cardiology and Cardiovascular Medicine 95
- Infectious Diseases 57
Countries citing papers authored by Abhirup Banerjee
This map shows the geographic impact of Abhirup Banerjee'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 Abhirup Banerjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhirup Banerjee more than expected).
Fields of papers citing papers by Abhirup Banerjee
This network shows the impact of papers produced by Abhirup Banerjee. 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 Abhirup Banerjee. The network helps show where Abhirup Banerjee may publish in the future.
Co-authorship network of co-authors of Abhirup Banerjee
This figure shows the co-authorship network connecting the top 25 collaborators of Abhirup Banerjee. A scholar is included among the top collaborators of Abhirup Banerjee 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 Abhirup Banerjee. Abhirup Banerjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 4 | |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 15 | |
| 18 | 18 | |
| 19 | 4 | |
| 20 | 7 |
About Abhirup Banerjee
Abhirup Banerjee is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging, having authored 51 papers that have together received 473 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (17 papers), 3D Shape Modeling and Analysis (8 papers) and Cardiac Imaging and Diagnostics (7 papers). The work is most often cited by research in Health Informatics (29 citations), Radiology, Nuclear Medicine and Imaging (208 citations) and Computer Vision and Pattern Recognition (139 citations). Abhirup Banerjee has collaborated with scholars based in United Kingdom, India and Australia. Frequent co-authors include Pradipta Maji, Vicente Grau, Marcel Beetz, Surajit Ray, Louise S. Mackenzie, Michail Mamalakis, Bart Vorselaars, Mark Baker, Robin P. Choudhury and Ernesto Zacur. Their work appears in journals such as Scientific Reports, International Journal of Molecular Sciences and IEEE Transactions on Image Processing.
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.