Dagmar Kainmueller
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Oral Surgery top 5%
- Surgery
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Stefan ZachowHans LameckerHans‐Christian HegeHeiko SeimMarkus O. HellerMax ZinserFlorian JugCarsten Rother
- Topics
- Medical Imaging and Analysis (7 papers)Medical Image Segmentation Techniques (5 papers)AI in cancer detection (5 papers)
- Cited by
- Oral SurgeryAgingBiophysics
- Partner nations
- GermanyUnited StatesFrance
In The Last Decade
Dagmar Kainmueller
26 papers receiving 324 citations
Peers
Comparison fields: 5 of 82
- Biomedical Engineering 129
- Computer Vision and Pattern Recognition 96
- Oral Surgery 83
- Surgery 63
- Radiology, Nuclear Medicine and Imaging 50
Countries citing papers authored by Dagmar Kainmueller
This map shows the geographic impact of Dagmar Kainmueller'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 Dagmar Kainmueller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dagmar Kainmueller more than expected).
Fields of papers citing papers by Dagmar Kainmueller
This network shows the impact of papers produced by Dagmar Kainmueller. 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 Dagmar Kainmueller. The network helps show where Dagmar Kainmueller may publish in the future.
Co-authorship network of co-authors of Dagmar Kainmueller
This figure shows the co-authorship network connecting the top 25 collaborators of Dagmar Kainmueller. A scholar is included among the top collaborators of Dagmar Kainmueller 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 Dagmar Kainmueller. Dagmar Kainmueller 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 | 4 | |
| 4 | 4 | |
| 5 | 16 | |
| 6 | 2 | |
| 7 | An Auxiliary Task for Learning Nuclei Segmentation in 3D Microscopy Images | 2 |
| 8 | 8 | |
| 9 | 9 | |
| 10 | 27 | |
| 11 | Deformable Meshes for Medical Image Segmentation: Accurate Automatic Segmentation of Anatomical Structures | 1 |
| 12 | Multi-object Segmentation with Coupled Deformable Models | 2 |
| 13 | 5 | |
| 14 | 16 | |
| 15 | 13 | |
| 16 | 2 | |
| 17 | 49 | |
| 18 | 0 | |
| 19 | 58 | |
| 20 | 70 |
About Dagmar Kainmueller
Dagmar Kainmueller is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Oral Surgery, having authored 27 papers that have together received 334 indexed citations. Recurring topics across this work include Medical Imaging and Analysis (7 papers), Medical Image Segmentation Techniques (5 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Oral Surgery (83 citations), Aging (11 citations) and Biophysics (30 citations). Dagmar Kainmueller has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Stefan Zachow, Hans Lamecker, Hans‐Christian Hege, Heiko Seim, Markus O. Heller, Max Zinser, Florian Jug, Carsten Rother, Eugene W. Myers and Gene Myers. Their work appears in journals such as Nature Biotechnology, Development and Scientific Reports.
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.