Dinggang Shen
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging
- Biomedical Engineering
- Artificial Intelligence
- Computational Mechanics
- Co-authors
- Christos DavatzikosXiaodong TaoPew‐Thian YapShen LiCarl‐Fredrik WestinTianming LiuPingkun YanKenji Suzuki
- Topics
- Brain Tumor Detection and Classification (4 papers)Medical Image Segmentation Techniques (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingGeometry and Topology
- Journals
- IEEE Transactions on Medical ImagingBiomedical Signal Processing and ControlLecture notes in computer science
- Partner nations
- United StatesChina
In The Last Decade
Dinggang Shen
6 papers receiving 210 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 156
- Radiology, Nuclear Medicine and Imaging 61
- Biomedical Engineering 52
- Artificial Intelligence 34
- Computational Mechanics 29
Countries citing papers authored by Dinggang Shen
This map shows the geographic impact of Dinggang Shen'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 Dinggang Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dinggang Shen more than expected).
Fields of papers citing papers by Dinggang Shen
This network shows the impact of papers produced by Dinggang Shen. 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 Dinggang Shen. The network helps show where Dinggang Shen may publish in the future.
Co-authorship network of co-authors of Dinggang Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Dinggang Shen. A scholar is included among the top collaborators of Dinggang Shen 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 Dinggang Shen. Dinggang Shen 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 6 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 31 | |
| 13 | 16 | |
| 14 | 139 | |
| 15 | 28 |
About Dinggang Shen
Dinggang Shen is a scholar working on Neurology, Computer Vision and Pattern Recognition and Biophysics, having authored 15 papers that have together received 221 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (4 papers), Medical Image Segmentation Techniques (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (156 citations), Radiology, Nuclear Medicine and Imaging (61 citations) and Geometry and Topology (22 citations). Dinggang Shen has collaborated with scholars based in United States and China. Frequent co-authors include Christos Davatzikos, Xiaodong Tao, Pew‐Thian Yap, Shen Li, Carl‐Fredrik Westin, Tianming Liu, Pingkun Yan, Kenji Suzuki, Fei Wang and Guorong Wu. Their work appears in journals such as IEEE Transactions on Medical Imaging, Biomedical Signal Processing and Control and Lecture notes in computer science.
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.