Simon Köhl
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 3
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- Anomaly Detection Techniques and Applications 2
- AI in cancer detection 2
- Co-authors
- Klaus Maier‐Hein (13 shared papers)Fabian Isensee (10 shared papers)Jens Petersen (5 shared papers)Paul F. Jaeger (3 shared papers)Sebastian Wirkert (2 shared papers)André Klein (2 shared papers)David Zimmerer (5 shared papers)Jakob Wasserthal (2 shared papers)
- Journals
- Radiology (2 papers)physica status solidi (b) (1 paper)Magnetic Resonance Imaging (1 paper)International Journal of Computer Assisted Radiology and Surgery (1 paper)Zenodo (CERN European Organization for Nuclear Research) (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Simon Köhl
14 papers receiving 1.0k citations
Simon Köhl's Hit Papers
Peers
Comparison fields: 5 of 87
- Health Informatics 45
- Radiology, Nuclear Medicine and Imaging 451
- Computer Vision and Pattern Recognition 321
- Neurology 92
- Pulmonary and Respiratory Medicine 337
Countries citing papers authored by Simon Köhl
This map shows the geographic impact of Simon Köhl'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 Simon Köhl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Köhl more than expected).
Fields of papers citing papers by Simon Köhl
This network shows the impact of papers produced by Simon Köhl. 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 Simon Köhl. The network helps show where Simon Köhl may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Köhl, 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 | Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation Hit paper breakdown → | 2019 | 413 |
| 2 | Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment Hit paper breakdown → | 2019 | 249 |
| 3 | 2018 | 159 | |
| 4 | nnU-Net: Breaking the Spell on Successful Medical Image Segmentation. | 2019 | 102 |
| 5 | Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection | 2020 | 44 |
| 6 | 2020 | 43 | |
| 7 | 2021 | 19 | |
| 8 | 2015 | 18 | |
| 9 | 2019 | 2 | |
| 10 | 2020 | 2 | |
| 11 | Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection | 2018 | 2 |
| 12 | 2020 | 1 | |
| 13 | 2020 | 1 | |
| 14 | 2024 | 1 |
About Simon Köhl
Simon Köhl is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Advanced Neural Network Applications (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Prostate Cancer Treatment and Research (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Medical Image Segmentation Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (45 citations), Radiology, Nuclear Medicine and Imaging (451 citations), Computer Vision and Pattern Recognition (321 citations), Neurology (92 citations) and Pulmonary and Respiratory Medicine (337 citations). Simon Köhl has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Klaus Maier‐Hein, Fabian Isensee, Jens Petersen, Paul F. Jaeger, Sebastian Wirkert, André Klein, David Zimmerer, Jakob Wasserthal, Tobias Norajitra and Gregor Koehler. Their work appears in journals such as Radiology, physica status solidi (b), Magnetic Resonance Imaging, International Journal of Computer Assisted Radiology and Surgery and Zenodo (CERN European Organization for Nuclear Research).
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.