Raphaël Prevost

636 citations
25 papers · 449 · h-index 9

Impact in

Papers in

Raphaël Prevost

25 papers receiving 437 citations

Peers

Raphaël Prevost
Comparison fields: 5 of 57
  • Computer Vision and Pattern Recognition 214
  • Radiology, Nuclear Medicine and Imaging 170
  • Health Informatics 6
  • Biomedical Engineering 156
  • Artificial Intelligence 66
Replace Athanasios Karamalis with:
Athanasios Karamalis Germany
Christian Daul France
Tobias Kunert Germany
Mark Hastenteufel Germany
Florian Link Germany
Nooshin Ghavami United Kingdom
Ali Islam Canada
Maysam Shahedi United States
Max W. K. Law Hong Kong
Tobias Norajitra Germany
Raphaël Prevost relative to Athanasios Karamalis Germany Athanasios Karamalis's profile →
Citations per field
00.5×2.6×
Athanasios Karamalis · 1×
Citations per year

Countries citing papers authored by Raphaël Prevost

Since Specialization
Citations

This map shows the geographic impact of Raphaël Prevost'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 Raphaël Prevost with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Prevost more than expected).

Fields of papers citing papers by Raphaël Prevost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raphaël Prevost. 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 Raphaël Prevost. The network helps show where Raphaël Prevost may publish in the future.

Co-authors

The 25 scholars most cited alongside Raphaël Prevost, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Raphaël Prevost Line = papers co-authored together Raphaël Prevost links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012133
2 2018104
3 201735
4 201734
5 201529
6 201222
7 202217
8 201315
9 202011
10 20137
11 20145
12 20135
13 20234
14 20234
15 20134
16 20144
17 20123
18
Template Deformation with User Constraints for Live 3D Interactive Surface Extraction
20112
19 20222
20
Deep Learning-Based 3D Freehand Ultrasound Reconstruction with Inertial Measurement Units
20182

About Raphaël Prevost

Raphaël Prevost is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Surgery and Computational Mechanics, having authored 25 papers that have together received 449 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (14 papers), Advanced Neural Network Applications (7 papers), Ultrasound Imaging and Elastography (4 papers), Medical Imaging and Analysis (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), MRI in cancer diagnosis (3 papers), Medical Imaging Techniques and Applications (3 papers) and Computer Graphics and Visualization Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (214 citations), Radiology, Nuclear Medicine and Imaging (170 citations), Health Informatics (6 citations), Biomedical Engineering (156 citations) and Artificial Intelligence (66 citations). Raphaël Prevost has collaborated with scholars based in France, Germany and United States. Frequent co-authors include Wolfgang Wein, Roberto Ardon, Benoît Mory, Mehrdad Salehi, Rémi Cuingnet, Laurent D. Cohen, David Lesage, Oliver Zettinig, Robert S. Bauer and Alexander Ladikos. Their work appears in journals such as Lecture notes in computer science, Medical Image Analysis, Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, Eurographics and UCL Discovery (University College London).

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.

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