Moritz Rempe
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 2
- MRI in cancer diagnosis 1
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- Digital Imaging for Blood Diseases 1
- Co-authors
- Fabian Hörst (4 shared papers)Jens Kleesiek (4 shared papers)Lukas Heine (3 shared papers)Jan Egger (3 shared papers)Giulia Baldini (1 shared paper)Constantin Seibold (3 shared papers)Julius Keyl (2 shared papers)Selma Ugurel (1 shared paper)
- Journals
- Computer Methods and Programs in Biomedicine (2 papers)European Radiology (1 paper)Medical Image Analysis (1 paper)Biomedizinische Technik/Biomedical Engineering (1 paper)Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition (1 paper)
In The Last Decade
Moritz Rempe
5 papers receiving 187 citations
Moritz Rempe's Hit Papers
Peers
Comparison fields: 5 of 43
- Biophysics 32
- Computer Vision and Pattern Recognition 57
- Artificial Intelligence 77
- Radiology, Nuclear Medicine and Imaging 38
- Neurology 13
Countries citing papers authored by Moritz Rempe
This map shows the geographic impact of Moritz Rempe'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 Moritz Rempe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moritz Rempe more than expected).
Fields of papers citing papers by Moritz Rempe
This network shows the impact of papers produced by Moritz Rempe. 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 Moritz Rempe. The network helps show where Moritz Rempe may publish in the future.
Co-authors
The 18 scholars most cited alongside Moritz Rempe, 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 | CellViT: Vision Transformers for precise cell segmentation and classification Hit paper breakdown → | 2024 | 161 |
| 2 | 2024 | 19 | |
| 3 | 2023 | 6 | |
| 4 | 2025 | 3 | |
| 5 | 2026 | 2 | |
| 6 | 2025 | 0 |
About Moritz Rempe
Moritz Rempe is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Artificial Intelligence and Insect Science, having authored 6 papers that have together received 191 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), MRI in cancer diagnosis (1 paper), AI in cancer detection (1 paper), Digital Imaging for Blood Diseases (1 paper) and Prostate Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Biophysics (32 citations), Computer Vision and Pattern Recognition (57 citations), Artificial Intelligence (77 citations), Radiology, Nuclear Medicine and Imaging (38 citations) and Neurology (13 citations). Moritz Rempe has collaborated with scholars based in Germany, Austria and Canada. Frequent co-authors include Fabian Hörst, Jens Kleesiek, Lukas Heine, Jan Egger, Giulia Baldini, Constantin Seibold, Julius Keyl, Selma Ugurel, Jens Thomas Siveke and Barbara T. Grünwald. Their work appears in journals such as Computer Methods and Programs in Biomedicine, European Radiology, Medical Image Analysis, Biomedizinische Technik/Biomedical Engineering and Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition.
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.