Stefan Heldmann

70 papers receiving 1.1k citations

Peers

Stefan Heldmann
Comparison fields: 5 of 109
  • Computer Vision and Pattern Recognition 429
  • Radiology, Nuclear Medicine and Imaging 260
  • Biophysics 67
  • Spectroscopy 184
  • Geophysics 120
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Countries citing papers authored by Stefan Heldmann

Since Specialization
Citations

This map shows the geographic impact of Stefan Heldmann'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 Stefan Heldmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Heldmann more than expected).

Fields of papers citing papers by Stefan Heldmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stefan Heldmann. 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 Stefan Heldmann. The network helps show where Stefan Heldmann may publish in the future.

Co-authors

The 25 scholars most cited alongside Stefan Heldmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefan Heldmann Line = papers co-authored together Stefan Heldmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012113
2 2008100
3 200698
4
Estimation of large motion in lung CT by integrating regularized keypoint correspondences into dense deformable registration
201778
5 201363
6 200659
7 201359
8 200759
9 201350
10 201137
11 201935
12 202134
13 201529
14 201624
15 201322
16 200822
17
Combining Automatic Landmark Detection and Variational Methods for Lung CT Registration
201320
18 200918
19 201915
20 200915

About Stefan Heldmann

Stefan Heldmann is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Computational Mechanics and Artificial Intelligence, having authored 75 papers that have together received 1.2k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (38 papers), Medical Imaging Techniques and Applications (23 papers), Medical Imaging and Analysis (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (6 papers), Advanced Radiotherapy Techniques (6 papers), Robotics and Sensor-Based Localization (5 papers) and 3D Shape Modeling and Analysis (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (429 citations), Radiology, Nuclear Medicine and Imaging (260 citations), Biophysics (67 citations), Spectroscopy (184 citations) and Geophysics (120 citations). Stefan Heldmann has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Eldad Haber, Jan Modersitzki, Bernd Fischer, Jan Rühaak, Stefan Wirtz, Nils Papenberg, Mattias P. Heinrich‬, Jan Strehlow, Alessa Hering and Uri M. Ascher. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, European Radiology, Medical Physics and SIAM Journal on Scientific Computing.

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.

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