Daniel Rinck

546 citations
10 papers · 391 · h-index 10

Impact in

Papers in

Daniel Rinck

10 papers receiving 373 citations

Peers

Daniel Rinck
Comparison fields: 5 of 42
  • Radiology, Nuclear Medicine and Imaging 188
  • Computer Vision and Pattern Recognition 146
  • Pulmonary and Respiratory Medicine 76
  • Computer Graphics and Computer-Aided Design 9
  • Cardiology and Cardiovascular Medicine 49
Replace Ameet Jain with:
Ameet Jain United States
Krishna Subramanyan United States
O. Wink Netherlands
Mehmet Gulsun United States
Milo Hindennach Germany
G.P.M. Prause Germany
Shigeru Eiho Japan
Onno Wink United States
Fei Mao United States
Fernando Vega-Higuera Germany
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Citations per field
00.5×2.9×
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Citations per year

Countries citing papers authored by Daniel Rinck

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Rinck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Rinck, 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 Daniel Rinck Line = papers co-authored together Daniel Rinck links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 200482
2 200574
3 200754
4 200648
5 200543
6 200624
7 200221
8 200521
9 200815
10 20069

About Daniel Rinck

Daniel Rinck is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Control and Systems Engineering and Atomic and Molecular Physics, and Optics, having authored 10 papers that have together received 391 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Cerebrovascular and Carotid Artery Diseases (3 papers), Cardiac Imaging and Diagnostics (3 papers), Advanced Neural Network Applications (2 papers), Medical Imaging Techniques and Applications (2 papers), Digital Image Processing Techniques (2 papers), Machine Fault Diagnosis Techniques (1 paper) and Blind Source Separation Techniques (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (188 citations), Computer Vision and Pattern Recognition (146 citations), Pulmonary and Respiratory Medicine (76 citations), Computer Graphics and Computer-Aided Design (9 citations) and Cardiology and Cardiovascular Medicine (49 citations). Daniel Rinck has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Michael Scheuering, Tobias Boskamp, Dominik Fritz, Florian Link, Georg Stamm, Peter Mildenberger, Thomas Flohr, Anja Reimann, Andreas H. Mahnken and Charles Florin. Their work appears in journals such as European Radiology, Investigative Radiology, Radiographics, International journal of cardiac imaging and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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