Ashirbani Saha
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Neurology top 5%
- Pulmonary and Respiratory Medicine top 10%
- Co-authors
- Maciej A. MazurowskiMateusz BudaMichael R. HarowiczMustafa R. BashirQ. M. Jonathan WuEhab A. AlBadawyZhe ZhuLars J. Grimm
- Topics
- Radiomics and Machine Learning in Medical Imaging (32 papers)AI in cancer detection (24 papers)MRI in cancer diagnosis (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Image ProcessingJournal of neurosurgery
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Ashirbani Saha
65 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Radiology, Nuclear Medicine and Imaging 1.3k
- Artificial Intelligence 890
- Computer Vision and Pattern Recognition 506
- Neurology 289
- Pulmonary and Respiratory Medicine 230
Countries citing papers authored by Ashirbani Saha
This map shows the geographic impact of Ashirbani Saha'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 Ashirbani Saha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashirbani Saha more than expected).
Fields of papers citing papers by Ashirbani Saha
This network shows the impact of papers produced by Ashirbani Saha. 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 Ashirbani Saha. The network helps show where Ashirbani Saha may publish in the future.
Co-authorship network of co-authors of Ashirbani Saha
This figure shows the co-authorship network connecting the top 25 collaborators of Ashirbani Saha. A scholar is included among the top collaborators of Ashirbani Saha 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 Ashirbani Saha. Ashirbani Saha 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 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 6 | |
| 6 | 58 | |
| 7 | 2 | |
| 8 | 14 | |
| 9 | 11 | |
| 10 | 16 | |
| 11 | 4 | |
| 12 | 4 | |
| 13 | Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRIbreakdown → | 362 |
| 14 | 187 | |
| 15 | 134 | |
| 16 | 39 | |
| 17 | 61 | |
| 18 | 32 | |
| 19 | 24 | |
| 20 | 15 |
About Ashirbani Saha
Ashirbani Saha is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 69 papers that have together received 2.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (32 papers), AI in cancer detection (24 papers) and MRI in cancer diagnosis (13 papers). The work is most often cited by research in Health Informatics (193 citations), Radiology, Nuclear Medicine and Imaging (1.3k citations) and Neurology (289 citations). Ashirbani Saha has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Maciej A. Mazurowski, Mateusz Buda, Michael R. Harowicz, Mustafa R. Bashir, Q. M. Jonathan Wu, Ehab A. AlBadawy, Zhe Zhu, Lars J. Grimm, Sujata V. Ghate and Ruth Walsh. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Journal of neurosurgery.
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.