Ratheesh Kalarot
- Radiology, Nuclear Medicine and Imaging top 10%
- Genetics
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Co-authors
- Birkan TunçHamed AkbariSarthak PatiChristos DavatzikosMark BergmanSpyridon BakasSaima RathoreDrew Parker
- Topics
- Advanced Vision and Imaging (5 papers)Advanced Image Processing Techniques (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)
- Journals
- Lecture notes in computer scienceJournal of Medical Imaging2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
- Partner nations
- New ZealandUnited StatesCanada
In The Last Decade
Ratheesh Kalarot
12 papers receiving 231 citations
Peers
Comparison fields: 5 of 72
- Radiology, Nuclear Medicine and Imaging 125
- Genetics 69
- Computer Vision and Pattern Recognition 67
- Pulmonary and Respiratory Medicine 28
- Biomedical Engineering 27
Countries citing papers authored by Ratheesh Kalarot
This map shows the geographic impact of Ratheesh Kalarot'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 Ratheesh Kalarot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ratheesh Kalarot more than expected).
Fields of papers citing papers by Ratheesh Kalarot
This network shows the impact of papers produced by Ratheesh Kalarot. 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 Ratheesh Kalarot. The network helps show where Ratheesh Kalarot may publish in the future.
Co-authorship network of co-authors of Ratheesh Kalarot
This figure shows the co-authorship network connecting the top 25 collaborators of Ratheesh Kalarot. A scholar is included among the top collaborators of Ratheesh Kalarot 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 Ratheesh Kalarot. Ratheesh Kalarot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 21 | |
| 4 | 8 | |
| 5 | 27 | |
| 6 | 129 | |
| 7 | 17 | |
| 8 | 8 | |
| 9 | Analysis of Real-Time Stereo Vision Algorithms On GPU | 7 |
| 10 | Implementation of Symmetric Dynamic Programming Stereo Matching Algorithm Using CUDA | 3 |
| 11 | 5 | |
| 12 | 2 |
About Ratheesh Kalarot
Ratheesh Kalarot is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Management and Media Technology, having authored 12 papers that have together received 233 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (5 papers), Advanced Image Processing Techniques (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Genetics (69 citations), Radiology, Nuclear Medicine and Imaging (125 citations) and Computer Vision and Pattern Recognition (67 citations). Ratheesh Kalarot has collaborated with scholars based in New Zealand, United States and Canada. Frequent co-authors include Birkan Tunç, Hamed Akbari, Sarthak Pati, Christos Davatzikos, Mark Bergman, Spyridon Bakas, Saima Rathore, Drew Parker, Eric A. Cohen and Nariman Jahani. Their work appears in journals such as Lecture notes in computer science, Journal of Medical Imaging and 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
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.