Jiang Tian
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Pulmonary and Respiratory Medicine
- Topics
- Medical Imaging and Analysis (4 papers)Advanced Neural Network Applications (4 papers)AI in cancer detection (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- NeurocomputingICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)University of Minnesota Digital Conservancy (University of Minnesota)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Jiang Tian
10 papers receiving 53 citations
Peers
Comparison fields: 5 of 25
- Artificial Intelligence 33
- Radiology, Nuclear Medicine and Imaging 29
- Computer Vision and Pattern Recognition 25
- Biomedical Engineering 10
- Pulmonary and Respiratory Medicine 9
Countries citing papers authored by Jiang Tian
This map shows the geographic impact of Jiang Tian'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 Jiang Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiang Tian more than expected).
Fields of papers citing papers by Jiang Tian
This network shows the impact of papers produced by Jiang Tian. 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 Jiang Tian. The network helps show where Jiang Tian may publish in the future.
Co-authorship network of co-authors of Jiang Tian
This figure shows the co-authorship network connecting the top 25 collaborators of Jiang Tian. A scholar is included among the top collaborators of Jiang Tian 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 Jiang Tian. Jiang Tian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 15 | |
| 10 | 13 | |
| 11 | Design and Realization of DICOM-based Medical Image Processing Software | 1 |
About Jiang Tian
Jiang Tian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management, having authored 11 papers that have together received 56 indexed citations. Recurring topics across this work include Medical Imaging and Analysis (4 papers), Advanced Neural Network Applications (4 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (29 citations), Computer Vision and Pattern Recognition (25 citations) and Artificial Intelligence (33 citations). Jiang Tian has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Cheng Zhong, Zhongchao Shi, Yao Zhang, Yixin Wang, Feng Hou, Jiawei Yang, Zhiqiang He, Zhiqiang He, Linhu Liu and Jianping Fan. Their work appears in journals such as Neurocomputing, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) and University of Minnesota Digital Conservancy (University of Minnesota).
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.