Fraunhofer Institute for Digital Medicine
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Medical Image Segmentation Techniques
Papers in
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- Medical Image Segmentation Techniques 382
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- Advanced MRI Techniques and Applications 146
- Radiomics and Machine Learning in Medical Imaging 60
- Medical Imaging Techniques and Applications 48
- Top scholars
- Heinz‐Otto PeitgenHorst Karl HahnBram van GinnekenMatthias GüntherDorit MerhofColin JacobsH HahnDavid H. Salat
- Journals
- International Journal of Computer Assisted Radiology and Surgery (52 papers)European Radiology (31 papers)PLoS ONE (27 papers)Medical Image Analysis (23 papers)Scientific Reports (22 papers)
- Partner nations
- GermanyNetherlandsUnited States
In The Last Decade
Fraunhofer Institute for Digital Medicine
1.2k papers receiving 32.8k citations
Peers
Comparison fields: 5 of 209
- Health Informatics 1k
- Computer Vision and Pattern Recognition 8.6k
- Radiology, Nuclear Medicine and Imaging 7.8k
- Computer Graphics and Computer-Aided Design 597
- Hepatology 1.1k
Countries citing scholars working at Fraunhofer Institute for Digital Medicine
This map shows the geographic impact of research produced by authors working at Fraunhofer Institute for Digital Medicine. 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 papers produced at Fraunhofer Institute for Digital Medicine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fraunhofer Institute for Digital Medicine more than expected).
Fields of papers published by authors at Fraunhofer Institute for Digital Medicine
This network shows the impact of papers affiliated with Fraunhofer Institute for Digital Medicine at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Fraunhofer Institute for Digital Medicine at the time of their publication.
About Fraunhofer Institute for Digital Medicine
In recent decades, authors affiliated with Fraunhofer Institute for Digital Medicine have published 1.3k papers, which have received a total of 32.9k indexed citations . Scholars at this organization have produced 439 papers in Computer Vision and Pattern Recognition, 336 papers in Radiology, Nuclear Medicine and Imaging, 36 papers in Health Informatics, 34 papers in Computer Graphics and Computer-Aided Design and 63 papers in Hepatology on the topics of Medical Image Segmentation Techniques (382 papers), Advanced MRI Techniques and Applications (146 papers), AI in cancer detection (81 papers), Anatomy and Medical Technology (63 papers), Radiomics and Machine Learning in Medical Imaging (60 papers), Hepatocellular Carcinoma Treatment and Prognosis (49 papers), Medical Imaging Techniques and Applications (48 papers) and Lung Cancer Diagnosis and Treatment (47 papers). Their work is cited by papers focused on Health Informatics (1k citations), Computer Vision and Pattern Recognition (8.6k citations), Radiology, Nuclear Medicine and Imaging (7.8k citations), Computer Graphics and Computer-Aided Design (597 citations) and Hepatology (1.1k citations). Authors at Fraunhofer Institute for Digital Medicine collaborate with scholars in Germany, Netherlands and United States and have published in prestigious journals including International Journal of Computer Assisted Radiology and Surgery, European Radiology, PLoS ONE, Medical Image Analysis and Scientific Reports. Some of Fraunhofer Institute for Digital Medicine's most productive authors include Heinz‐Otto Peitgen, Horst Karl Hahn, Bram van Ginneken, Matthias Günther, Dorit Merhof, Colin Jacobs, H Hahn, David H. Salat, Evelina Busa and Anders Martin Dale.
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.