Suprosanna Shit
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Biophysics top 5%
- Artificial Intelligence
- Co-authors
- Bjoern MenzeJohannes C. PaetzoldAli ErtürkOliver SchoppeMarie PiraudMihail Ivilinov TodorovMarco DüringGiles Tetteh
- Topics
- Medical Image Segmentation Techniques (4 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Medical Imaging and Analysis (4 papers)
- Partner nations
- GermanySwitzerlandUnited Kingdom
In The Last Decade
Suprosanna Shit
25 papers receiving 462 citations
Peers
Comparison fields: 5 of 85
- Radiology, Nuclear Medicine and Imaging 171
- Computer Vision and Pattern Recognition 126
- Biomedical Engineering 97
- Biophysics 91
- Artificial Intelligence 65
Countries citing papers authored by Suprosanna Shit
This map shows the geographic impact of Suprosanna Shit'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 Suprosanna Shit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suprosanna Shit more than expected).
Fields of papers citing papers by Suprosanna Shit
This network shows the impact of papers produced by Suprosanna Shit. 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 Suprosanna Shit. The network helps show where Suprosanna Shit may publish in the future.
Co-authorship network of co-authors of Suprosanna Shit
This figure shows the co-authorship network connecting the top 25 collaborators of Suprosanna Shit. A scholar is included among the top collaborators of Suprosanna Shit 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 Suprosanna Shit. Suprosanna Shit 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 | 7 | |
| 3 | 2 | |
| 4 | 14 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 8 | |
| 11 | 14 | |
| 12 | 14 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 3 | |
| 16 | 2 | |
| 17 | 18 | |
| 18 | 13 | |
| 19 | 61 | |
| 20 | 205 |
About Suprosanna Shit
Suprosanna Shit is a scholar working on Health Informatics, Biophysics and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 469 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Medical Imaging and Analysis (4 papers). The work is most often cited by research in Biophysics (91 citations), Radiology, Nuclear Medicine and Imaging (171 citations) and Computer Vision and Pattern Recognition (126 citations). Suprosanna Shit has collaborated with scholars based in Germany, Switzerland and United Kingdom. Frequent co-authors include Bjoern Menze, Johannes C. Paetzold, Ali Ertürk, Oliver Schoppe, Marie Piraud, Mihail Ivilinov Todorov, Marco Düring, Giles Tetteh, Katalin Völgyi and Martin Dichgans. Their work appears in journals such as Nature Methods, IEEE Transactions on Medical Imaging and Human Brain Mapping.
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.