Junjie Bai
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Surgery
- Ophthalmology top 10%
- Co-authors
- Xiaodong WuMilan SonkaQi SongMona K. GarvinJohn M. BuattiXin LiuDan WuXin Wang
- Topics
- Medical Image Segmentation Techniques (8 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Medical Imaging Techniques and Applications (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionOphthalmology
- Journals
- International Journal of Radiation Oncology*Biology*PhysicsIEEE Transactions on Medical ImagingPhysics in Medicine and Biology
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Junjie Bai
14 papers receiving 288 citations
Peers
Comparison fields: 5 of 54
- Radiology, Nuclear Medicine and Imaging 146
- Computer Vision and Pattern Recognition 111
- Biomedical Engineering 92
- Surgery 63
- Ophthalmology 48
Countries citing papers authored by Junjie Bai
This map shows the geographic impact of Junjie Bai'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 Junjie Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junjie Bai more than expected).
Fields of papers citing papers by Junjie Bai
This network shows the impact of papers produced by Junjie Bai. 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 Junjie Bai. The network helps show where Junjie Bai may publish in the future.
Co-authorship network of co-authors of Junjie Bai
This figure shows the co-authorship network connecting the top 25 collaborators of Junjie Bai. A scholar is included among the top collaborators of Junjie Bai 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 Junjie Bai. Junjie Bai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 86 | |
| 4 | 3 | |
| 5 | 5 | |
| 6 | 6 | |
| 7 | 39 | |
| 8 | 7 | |
| 9 | 47 | |
| 10 | 6 | |
| 11 | 4 | |
| 12 | 74 | |
| 13 | 2 | |
| 14 | 12 |
About Junjie Bai
Junjie Bai is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Radiation, having authored 14 papers that have together received 294 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Medical Imaging Techniques and Applications (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (146 citations), Computer Vision and Pattern Recognition (111 citations) and Ophthalmology (48 citations). Junjie Bai has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Xiaodong Wu, Milan Sonka, Qi Song, Mona K. Garvin, John M. Buatti, Xin Liu, Dan Wu, Xin Wang, Victor Hugo C. de Albuquerque and Guoyan Zheng. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, IEEE Transactions on Medical Imaging and Physics in Medicine and Biology.
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.