Klaus Maier‐Hein
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- Radiomics and Machine Learning in Medical Imaging 47
- Advanced Neuroimaging Techniques and Applications 37
- Advanced MRI Techniques and Applications 26
- MRI in cancer diagnosis 24
- Health Informatics top 0.5%
- Neurology top 1%
- Computational Mathematics top 5%
- Genetics top 2%
- Glioma Diagnosis and Treatment 15
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- Functional Brain Connectivity Studies 17
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- Medical Imaging and Analysis 14
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- AI in cancer detection 13
Klaus Maier‐Hein
159 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Radiology, Nuclear Medicine and Imaging 3.9k
- Health Informatics 148
- Neurology 581
- Computational Mathematics 32
- Genetics 513
Countries citing papers authored by Klaus Maier‐Hein
This map shows the geographic impact of Klaus Maier‐Hein'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 Klaus Maier‐Hein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Klaus Maier‐Hein more than expected).
Fields of papers citing papers by Klaus Maier‐Hein
This network shows the impact of papers produced by Klaus Maier‐Hein. 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 Klaus Maier‐Hein. The network helps show where Klaus Maier‐Hein may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Klaus Maier‐Hein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 15 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 6 | |
| 10 | 2022 | 32 | |
| 11 | 2022 | 7 | |
| 12 | 2022 | 9 | |
| 13 | 2022 | 15 | |
| 14 | 2020 | 9 | |
| 15 | 2020 | 17 | |
| 16 | Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessmentbreakdown → | 2019 | 230 |
| 17 | nnU-Net: Breaking the Spell on Successful Medical Image Segmentation. | 2019 | 84 |
| 18 | 2016 | 206 | |
| 19 | 2016 | 13 | |
| 20 | 2015 | 53 |
About Klaus Maier‐Hein
Klaus Maier‐Hein is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Genetics, having authored 167 papers that have together received 5.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (47 papers), Advanced Neuroimaging Techniques and Applications (37 papers), Advanced MRI Techniques and Applications (26 papers), MRI in cancer diagnosis (24 papers), Functional Brain Connectivity Studies (17 papers), Glioma Diagnosis and Treatment (15 papers), Medical Imaging and Analysis (14 papers) and AI in cancer detection (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (3.9k citations), Health Informatics (148 citations) and Neurology (581 citations). Klaus Maier‐Hein has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Peter Neher, Bram Stieltjes, Jakob Wasserthal, Martin Bendszus, David Bonekamp, Philipp Kickingereder, Frederik B. Laun, Michael Götz, Fabian Isensee and Dušan Hirjak. Their work appears in journals such as Scientific Reports, European Radiology, Medical Image Analysis, International Journal of Computer Assisted Radiology and Surgery and NeuroImage.
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.