Mehul Sampat
- Computer Vision and Pattern Recognition top 2%
- Pathology and Forensic Medicine top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Media Technology top 2%
- Co-authors
- Alan C. BovikMia K. MarkeyZhou WangShalini GuptaGary J. WhitmanChristina AzevedoDarin T. OkudaDaniel Pelletier
- Topics
- AI in cancer detection (12 papers)Multiple Sclerosis Research Studies (8 papers)Medical Imaging Techniques and Applications (6 papers)
- Partner nations
- United StatesFranceItaly
In The Last Decade
Mehul Sampat
37 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Computer Vision and Pattern Recognition 504
- Pathology and Forensic Medicine 347
- Radiology, Nuclear Medicine and Imaging 272
- Artificial Intelligence 246
- Media Technology 190
Countries citing papers authored by Mehul Sampat
This map shows the geographic impact of Mehul Sampat'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 Mehul Sampat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mehul Sampat more than expected).
Fields of papers citing papers by Mehul Sampat
This network shows the impact of papers produced by Mehul Sampat. 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 Mehul Sampat. The network helps show where Mehul Sampat may publish in the future.
Co-authorship network of co-authors of Mehul Sampat
This figure shows the co-authorship network connecting the top 25 collaborators of Mehul Sampat. A scholar is included among the top collaborators of Mehul Sampat 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 Mehul Sampat. Mehul Sampat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 86 | |
| 3 | 1 | |
| 4 | Comparison of SUVR Methods and Reference Regions in Amyloid PET | 5 |
| 5 | 5 | |
| 6 | 19 | |
| 7 | 26 | |
| 8 | 1 | |
| 9 | Complex Wavelet Structural Similarity: A New Image Similarity Indexbreakdown → | 436 |
| 10 | 10 | |
| 11 | 39 | |
| 12 | 28 | |
| 13 | 37 | |
| 14 | 8 | |
| 15 | 12 | |
| 16 | 2 | |
| 17 | 50 | |
| 18 | 7 | |
| 19 | 1 | |
| 20 | 3 |
About Mehul Sampat
Mehul Sampat is a scholar working on Pathology and Forensic Medicine, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 37 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Multiple Sclerosis Research Studies (8 papers) and Medical Imaging Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (504 citations), Media Technology (190 citations) and Pathology and Forensic Medicine (347 citations). Mehul Sampat has collaborated with scholars based in United States, France and Italy. Frequent co-authors include Alan C. Bovik, Mia K. Markey, Zhou Wang, Shalini Gupta, Gary J. Whitman, Christina Azevedo, Darin T. Okuda, Daniel Pelletier, Kenneth R. Castleman and T.W. Stephens. Their work appears in journals such as NeuroImage, Neurology and Annals of Neurology.
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.