Stefan Leger
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Health Informatics top 2%
Papers in
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- Radiomics and Machine Learning in Medical Imaging 13
- Medical Imaging Techniques and Applications 4
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- Head and Neck Cancer Studies 4
- Co-authors
- Stefanie Speidel (6 shared papers)Steffen Löck (8 shared papers)Jürgen Weitz (5 shared papers)Fiona R. Kolbinger (4 shared papers)Marius Distler (4 shared papers)Alex Zwanenburg (5 shared papers)Mechthild Krause (4 shared papers)Sebastian Bodenstedt (2 shared papers)
In The Last Decade
Stefan Leger
20 papers receiving 3.4k citations
Stefan Leger's Hit Papers
Peers
Comparison fields: 5 of 91
- Radiology, Nuclear Medicine and Imaging 2.0k
- Health Informatics 101
- Otorhinolaryngology 112
- Pulmonary and Respiratory Medicine 569
- Genetics 185
Countries citing papers authored by Stefan Leger
This map shows the geographic impact of Stefan Leger'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 Leger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Leger more than expected).
Fields of papers citing papers by Stefan Leger
This network shows the impact of papers produced by Stefan Leger. 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 Leger. The network helps show where Stefan Leger may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefan Leger, 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 | The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping Hit paper breakdown → | 2020 | 2879 |
| 2 | 2017 | 172 | |
| 3 | 2020 | 68 | |
| 4 | 2020 | 48 | |
| 5 | 2018 | 43 | |
| 6 | 2018 | 40 | |
| 7 | 2023 | 29 | |
| 8 | 2022 | 25 | |
| 9 | 2022 | 25 | |
| 10 | 2023 | 25 | |
| 11 | 2020 | 23 | |
| 12 | 1983 | 22 | |
| 13 | 2023 | 13 | |
| 14 | 2020 | 11 | |
| 15 | 2017 | 9 | |
| 16 | 2017 | 7 | |
| 17 | 2020 | 7 | |
| 18 | 2020 | 5 | |
| 19 | 2020 | 3 | |
| 20 | 2015 | 2 |
About Stefan Leger
Stefan Leger is a scholar working on Radiology, Nuclear Medicine and Imaging, Otorhinolaryngology, Oncology, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine, having authored 20 papers that have together received 3.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), Head and Neck Cancer Studies (4 papers), Medical Imaging Techniques and Applications (4 papers), Pancreatic and Hepatic Oncology Research (3 papers), Colorectal Cancer Surgical Treatments (2 papers), Medical Image Segmentation Techniques (2 papers), Lung Cancer Diagnosis and Treatment (2 papers) and Cerebrospinal fluid and hydrocephalus (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.0k citations), Health Informatics (101 citations), Otorhinolaryngology (112 citations), Pulmonary and Respiratory Medicine (569 citations) and Genetics (185 citations). Stefan Leger has collaborated with scholars based in Germany, Hong Kong and Colombia. Frequent co-authors include Stefanie Speidel, Steffen Löck, Jürgen Weitz, Fiona R. Kolbinger, Marius Distler, Alex Zwanenburg, Mechthild Krause, Sebastian Bodenstedt, Jens‐Peter Kühn and Daniel Zips. Their work appears in journals such as Scientific Reports, Radiotherapy and Oncology, Physics and Imaging in Radiation Oncology, Clinical and Translational Radiation Oncology and Medical Image Analysis.
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.