Eri Matsuyama
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Pulmonary and Respiratory Medicine
- Co-authors
- Du‐Yih TsaiYongbum LeeNoriyuki TakahashiToshibumi KinoshitaKiyoshi IshiiHsian‐Min ChenMegumi TakeharaHideto Toyoshima
- Topics
- AI in cancer detection (12 papers)Digital Radiography and Breast Imaging (9 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)
In The Last Decade
Eri Matsuyama
23 papers receiving 454 citations
Peers
Comparison fields: 5 of 100
- Computer Vision and Pattern Recognition 208
- Media Technology 112
- Artificial Intelligence 110
- Radiology, Nuclear Medicine and Imaging 100
- Pulmonary and Respiratory Medicine 76
Countries citing papers authored by Eri Matsuyama
This map shows the geographic impact of Eri Matsuyama'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 Eri Matsuyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eri Matsuyama more than expected).
Fields of papers citing papers by Eri Matsuyama
This network shows the impact of papers produced by Eri Matsuyama. 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 Eri Matsuyama. The network helps show where Eri Matsuyama may publish in the future.
Co-authorship network of co-authors of Eri Matsuyama
This figure shows the co-authorship network connecting the top 25 collaborators of Eri Matsuyama. A scholar is included among the top collaborators of Eri Matsuyama 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 Eri Matsuyama. Eri Matsuyama 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 | 1 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 4 | |
| 7 | 18 | |
| 8 | 17 | |
| 9 | 2 | |
| 10 | 45 | |
| 11 | 12 | |
| 12 | 27 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 3 | |
| 16 | 5 | |
| 17 | Image Quality Evaluation of Digital Radiographs by Use of Transmitted Information Metric | 1 |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 280 |
About Eri Matsuyama
Eri Matsuyama is a scholar working on Media Technology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 471 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Digital Radiography and Breast Imaging (9 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Media Technology (112 citations), Computer Vision and Pattern Recognition (208 citations) and Health Informatics (7 citations). Eri Matsuyama has collaborated with scholars based in Japan, Taiwan and Australia. Frequent co-authors include Du‐Yih Tsai, Yongbum Lee, Noriyuki Takahashi, Toshibumi Kinoshita, Kiyoshi Ishii, Hsian‐Min Chen, Megumi Takehara and Hideto Toyoshima. Their work appears in journals such as Journal of Digital Imaging, Journal of Electronic Imaging and International Journal of Biomedical 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.