Matthias Elter
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Molecular Biology
- Pulmonary and Respiratory Medicine
- Co-authors
- Thomas WittenbergAlexander HorschR Schulz-WendtlandChristian WinterChristian MünzenmayerChristian HeldAlexander HapfelmeierFlorian Wagner
- Topics
- AI in cancer detection (13 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Biomedical Text Mining and Ontologies (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Partner nations
- GermanyNorwayUnited States
In The Last Decade
Matthias Elter
25 papers receiving 587 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 406
- Computer Vision and Pattern Recognition 236
- Radiology, Nuclear Medicine and Imaging 232
- Molecular Biology 92
- Pulmonary and Respiratory Medicine 90
Countries citing papers authored by Matthias Elter
This map shows the geographic impact of Matthias Elter'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 Matthias Elter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Elter more than expected).
Fields of papers citing papers by Matthias Elter
This network shows the impact of papers produced by Matthias Elter. 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 Matthias Elter. The network helps show where Matthias Elter may publish in the future.
Co-authorship network of co-authors of Matthias Elter
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Elter. A scholar is included among the top collaborators of Matthias Elter 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 Matthias Elter. Matthias Elter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 59 | |
| 2 | 28 | |
| 3 | 1 | |
| 4 | 40 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 4 | |
| 8 | 144 | |
| 9 | 1 | |
| 10 | 13 | |
| 11 | 2 | |
| 12 | 11 | |
| 13 | 0 | |
| 14 | 8 | |
| 15 | 12 | |
| 16 | 192 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 46 | |
| 20 | 17 |
About Matthias Elter
Matthias Elter is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 620 indexed citations. Recurring topics across this work include AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (406 citations), Computer Vision and Pattern Recognition (236 citations) and Radiology, Nuclear Medicine and Imaging (232 citations). Matthias Elter has collaborated with scholars based in Germany, Norway and United States. Frequent co-authors include Thomas Wittenberg, Alexander Horsch, R Schulz-Wendtland, Christian Winter, Christian Münzenmayer, Christian Held, Alexander Hapfelmeier, Florian Wagner, Rüdiger Schulz‐Wendtland and Christian R. Loehberg. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Physics in Medicine and Biology and Medical Physics.
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.