Ingrid C. Sluimer
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
- Neurology top 5%
Papers in
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- Radiomics and Machine Learning in Medical Imaging 3
- Medical Imaging Techniques and Applications 3
- COVID-19 diagnosis using AI 2
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- Medical Image Segmentation Techniques 3
- Co-authors
- Bram van Ginneken (6 shared papers)Mathias Prokop (3 shared papers)Arnold M. R. Schilham (1 shared paper)Hugo Vrenken (5 shared papers)Frederik Barkhof (5 shared papers)Wiesje M. van der Flier (4 shared papers)Wouter J.P. Henneman (3 shared papers)Philip Scheltens (3 shared papers)
- Journals
- Neurology (3 papers)IEEE Transactions on Medical Imaging (2 papers)Medical Physics (2 papers)Human Brain Mapping (1 paper)NeuroImage (1 paper)
- Partner nations
- NetherlandsUnited KingdomItaly
In The Last Decade
Ingrid C. Sluimer
11 papers receiving 1.4k citations
Ingrid C. Sluimer's Hit Papers
Peers
Comparison fields: 5 of 92
- Radiology, Nuclear Medicine and Imaging 663
- Neurology 137
- Psychiatry and Mental health 205
- Pulmonary and Respiratory Medicine 431
- Computer Vision and Pattern Recognition 304
Countries citing papers authored by Ingrid C. Sluimer
This map shows the geographic impact of Ingrid C. Sluimer'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 Ingrid C. Sluimer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ingrid C. Sluimer more than expected).
Fields of papers citing papers by Ingrid C. Sluimer
This network shows the impact of papers produced by Ingrid C. Sluimer. 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 Ingrid C. Sluimer. The network helps show where Ingrid C. Sluimer may publish in the future.
Co-authors
The 25 scholars most cited alongside Ingrid C. Sluimer, 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 | Computer analysis of computed tomography scans of the lung: a survey Hit paper breakdown → | 2006 | 431 |
| 2 | 2009 | 288 | |
| 3 | 2005 | 202 | |
| 4 | 2012 | 139 | |
| 5 | 2003 | 123 | |
| 6 | 2010 | 105 | |
| 7 | 2009 | 63 | |
| 8 | 2006 | 53 | |
| 9 | 2013 | 35 | |
| 10 | 2004 | 18 | |
| 11 | 2002 | 1 |
About Ingrid C. Sluimer
Ingrid C. Sluimer is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Artificial Intelligence and Psychiatry and Mental health, having authored 11 papers that have together received 1.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (3 papers), Medical Imaging Techniques and Applications (3 papers), COVID-19 diagnosis using AI (2 papers), AI in cancer detection (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Dementia and Cognitive Impairment Research (2 papers) and Nuclear Physics and Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (663 citations), Neurology (137 citations), Psychiatry and Mental health (205 citations), Pulmonary and Respiratory Medicine (431 citations) and Computer Vision and Pattern Recognition (304 citations). Ingrid C. Sluimer has collaborated with scholars based in Netherlands, United Kingdom and Italy. Frequent co-authors include Bram van Ginneken, Mathias Prokop, Arnold M. R. Schilham, Hugo Vrenken, Frederik Barkhof, Wiesje M. van der Flier, Wouter J.P. Henneman, Philip Scheltens, Jasper D. Sluimer and Josephine Barnes. Their work appears in journals such as Neurology, IEEE Transactions on Medical Imaging, Medical Physics, Human Brain Mapping 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.