Florian Dubost
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Cognitive Neuroscience
- Pediatrics, Perinatology and Child Health
- Co-authors
- Marleen de BruijneMeike W. VernooijM. Arfan IkramHieab H.H. AdamsWiro J. NiessenGerda BortsovaMaria J. KnolPınar Yilmaz
- Topics
- Medical Image Segmentation Techniques (5 papers)Medical Imaging and Analysis (3 papers)Cerebrospinal fluid and hydrocephalus (3 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingCellular and Molecular Neuroscience
- Partner nations
- NetherlandsDenmarkUnited States
In The Last Decade
Florian Dubost
14 papers receiving 415 citations
Peers
Comparison fields: 5 of 84
- Radiology, Nuclear Medicine and Imaging 130
- Artificial Intelligence 94
- Cellular and Molecular Neuroscience 87
- Cognitive Neuroscience 74
- Pediatrics, Perinatology and Child Health 71
Countries citing papers authored by Florian Dubost
This map shows the geographic impact of Florian Dubost'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 Florian Dubost with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Dubost more than expected).
Fields of papers citing papers by Florian Dubost
This network shows the impact of papers produced by Florian Dubost. 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 Florian Dubost. The network helps show where Florian Dubost may publish in the future.
Co-authorship network of co-authors of Florian Dubost
This figure shows the co-authorship network connecting the top 25 collaborators of Florian Dubost. A scholar is included among the top collaborators of Florian Dubost based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Florian Dubost. Florian Dubost is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 12 | |
| 3 | 34 | |
| 4 | 18 | |
| 5 | 14 | |
| 6 | 54 | |
| 7 | 11 | |
| 8 | 19 | |
| 9 | 37 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset. | 1 |
| 13 | Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data. | 1 |
| 14 | 130 | |
| 15 | 0 | |
| 16 | 74 |
About Florian Dubost
Florian Dubost is a scholar working on Computer Vision and Pattern Recognition, Neurology and Cellular and Molecular Neuroscience, having authored 16 papers that have together received 419 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Medical Imaging and Analysis (3 papers) and Cerebrospinal fluid and hydrocephalus (3 papers). The work is most often cited by research in Health Informatics (25 citations), Radiology, Nuclear Medicine and Imaging (130 citations) and Cellular and Molecular Neuroscience (87 citations). Florian Dubost has collaborated with scholars based in Netherlands, Denmark and United States. Frequent co-authors include Marleen de Bruijne, Meike W. Vernooij, M. Arfan Ikram, Hieab H.H. Adams, Wiro J. Niessen, Gerda Bortsova, Maria J. Knol, Pınar Yilmaz, Aleksei Tiulpin and Gennady V. Roshchupkin. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Neurology.
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.