Binjie Qin
- Radiology, Nuclear Medicine and Imaging top 5%
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Pulmonary and Respiratory Medicine
- Topics
- Medical Image Segmentation Techniques (11 papers)Advanced MRI Techniques and Applications (5 papers)Photoacoustic and Ultrasonic Imaging (5 papers)
- Cited by
- Computational MathematicsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Binjie Qin
33 papers receiving 748 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 351
- Biomedical Engineering 228
- Computer Vision and Pattern Recognition 226
- Artificial Intelligence 158
- Pulmonary and Respiratory Medicine 104
Countries citing papers authored by Binjie Qin
This map shows the geographic impact of Binjie Qin'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 Binjie Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binjie Qin more than expected).
Fields of papers citing papers by Binjie Qin
This network shows the impact of papers produced by Binjie Qin. 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 Binjie Qin. The network helps show where Binjie Qin may publish in the future.
Co-authorship network of co-authors of Binjie Qin
This figure shows the co-authorship network connecting the top 25 collaborators of Binjie Qin. A scholar is included among the top collaborators of Binjie Qin 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 Binjie Qin. Binjie Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 3 | |
| 3 | 20 | |
| 4 | 21 | |
| 5 | 47 | |
| 6 | 12 | |
| 7 | 24 | |
| 8 | 31 | |
| 9 | 31 | |
| 10 | 8 | |
| 11 | Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Reviewbreakdown → | 334 |
| 12 | 2 | |
| 13 | 16 | |
| 14 | 6 | |
| 15 | 7 | |
| 16 | 1 | |
| 17 | 10 | |
| 18 | 1 | |
| 19 | 0 | |
| 20 | 14 |
About Binjie Qin
Binjie Qin is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 37 papers that have together received 759 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (11 papers), Advanced MRI Techniques and Applications (5 papers) and Photoacoustic and Ultrasonic Imaging (5 papers). The work is most often cited by research in Computational Mathematics (14 citations), Radiology, Nuclear Medicine and Imaging (351 citations) and Computer Vision and Pattern Recognition (226 citations). Binjie Qin has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Baowei Fei, Guolan Lu, Rongrong Guo, Yisong Lv, Qiegen Liu, Yueqi Zhu, Song Ding, Dong Liang, Jian Jiang and Jun Zhao. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Access and IEEE Transactions on Medical Imaging.
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.