Anup Sadhu
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Neurology top 10%
- Co-authors
- Debangshu DeyJayasree ChakrabortySudipta MukhopadhyayAbhishek MidyaDebashis NandiPranab Kumar DuttaChandan ChakrabortyNiranjan Khandelwal
- Topics
- AI in cancer detection (17 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)Medical Image Segmentation Techniques (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Access
- Partner nations
- IndiaUnited StatesCanada
In The Last Decade
Anup Sadhu
38 papers receiving 395 citations
Peers
Comparison fields: 5 of 72
- Radiology, Nuclear Medicine and Imaging 209
- Artificial Intelligence 154
- Computer Vision and Pattern Recognition 127
- Pulmonary and Respiratory Medicine 123
- Neurology 64
Countries citing papers authored by Anup Sadhu
This map shows the geographic impact of Anup Sadhu'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 Anup Sadhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anup Sadhu more than expected).
Fields of papers citing papers by Anup Sadhu
This network shows the impact of papers produced by Anup Sadhu. 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 Anup Sadhu. The network helps show where Anup Sadhu may publish in the future.
Co-authorship network of co-authors of Anup Sadhu
This figure shows the co-authorship network connecting the top 25 collaborators of Anup Sadhu. A scholar is included among the top collaborators of Anup Sadhu 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 Anup Sadhu. Anup Sadhu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 28 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 12 | |
| 6 | 73 | |
| 7 | 7 | |
| 8 | 35 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 14 | |
| 12 | 9 | |
| 13 | 6 | |
| 14 | 19 | |
| 15 | 7 | |
| 16 | 9 | |
| 17 | 2 | |
| 18 | 15 | |
| 19 | 15 | |
| 20 | 2 |
About Anup Sadhu
Anup Sadhu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 40 papers that have together received 404 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Medical Image Segmentation Techniques (10 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (209 citations), Neurology (64 citations) and Computer Vision and Pattern Recognition (127 citations). Anup Sadhu has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Debangshu Dey, Jayasree Chakraborty, Sudipta Mukhopadhyay, Abhishek Midya, Debashis Nandi, Pranab Kumar Dutta, Chandan Chakraborty, Niranjan Khandelwal, Pabitra Mitra and Palash Ghosal. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.
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.