Dagan Feng
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Media Technology top 5%
- Co-authors
- Michael FulhamJinman KimAshnil KumarXinmin WangSung-Cheng HuangYong XiaKewei ChenTianjiao Wang
- Topics
- Medical Imaging Techniques and Applications (16 papers)Advanced MRI Techniques and Applications (9 papers)Medical Image Segmentation Techniques (7 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionMedia Technology
In The Last Decade
Dagan Feng
29 papers receiving 986 citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Radiology, Nuclear Medicine and Imaging 520
- Computer Vision and Pattern Recognition 329
- Artificial Intelligence 236
- Biomedical Engineering 108
- Media Technology 100
Countries citing papers authored by Dagan Feng
This map shows the geographic impact of Dagan Feng'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 Dagan Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dagan Feng more than expected).
Fields of papers citing papers by Dagan Feng
This network shows the impact of papers produced by Dagan Feng. 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 Dagan Feng. The network helps show where Dagan Feng may publish in the future.
Co-authorship network of co-authors of Dagan Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Dagan Feng. A scholar is included among the top collaborators of Dagan Feng 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 Dagan Feng. Dagan Feng 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 | 0 | |
| 3 | An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classificationbreakdown → | 382 |
| 4 | 19 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 82 | |
| 10 | 35 | |
| 11 | 2 | |
| 12 | 10 | |
| 13 | 1 | |
| 14 | 9 | |
| 15 | 11 | |
| 16 | 7 | |
| 17 | 24 | |
| 18 | 28 | |
| 19 | 65 | |
| 20 | 187 |
About Dagan Feng
Dagan Feng is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 33 papers that have together received 1.0k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (16 papers), Advanced MRI Techniques and Applications (9 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (520 citations), Computer Vision and Pattern Recognition (329 citations) and Media Technology (100 citations). Dagan Feng has collaborated with scholars based in Australia, Hong Kong and China. Frequent co-authors include Michael Fulham, Jinman Kim, Ashnil Kumar, Xinmin Wang, Sung-Cheng Huang, Yong Xia, Kewei Chen, Tianjiao Wang, Yanning Zhang and Yong Xia. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Biomedical Engineering 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.