Benoît Scherrer

2.4k citations
79 papers · 1.6k · h-index 24

Impact in

Papers in

Benoît Scherrer

78 papers receiving 1.6k citations

Peers

Benoît Scherrer
Comparison fields: 5 of 104
  • Computational Mathematics 56
  • Radiology, Nuclear Medicine and Imaging 737
  • Pediatrics, Perinatology and Child Health 286
  • Physiology 288
  • Neurology 89
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Marina Barysheva United States
Yan Jin United States
Anil Rao United Kingdom
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Eleftherios Garyfallidis United States
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Peter Savadjiev United States
M. Okan İrfanoğlu United States
Brad Davis United States
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Citations per field
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Citations per year

Countries citing papers authored by Benoît Scherrer

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Scherrer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Benoît Scherrer, 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 Benoît Scherrer Line = papers co-authored together Benoît Scherrer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011109
2 2012104
3 201582
4 200781
5 201976
6 201264
7 201260
8 201759
9 200958
10 201643
11 202139
12 201935
13 201634
14 201832
15 201931
16 201331
17 201331
18 201728
19 202027
20 201027

About Benoît Scherrer

Benoît Scherrer is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Physiology, Computer Vision and Pattern Recognition and Molecular Biology, having authored 79 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (39 papers), Advanced MRI Techniques and Applications (25 papers), Fetal and Pediatric Neurological Disorders (18 papers), MRI in cancer diagnosis (14 papers), Tuberous Sclerosis Complex Research (10 papers), Medical Image Segmentation Techniques (9 papers), Tensor decomposition and applications (7 papers) and Functional Brain Connectivity Studies (6 papers). The work is most often cited by research in Computational Mathematics (56 citations), Radiology, Nuclear Medicine and Imaging (737 citations), Pediatrics, Perinatology and Child Health (286 citations), Physiology (288 citations) and Neurology (89 citations). Benoît Scherrer has collaborated with scholars based in United States, France and Belgium. Frequent co-authors include Simon K. Warfield, Mustafa Şahin, Ali Gholipour, Sanjay P. Prabhu, Maxime Taquet, Jurriaan M. Peters, Michel Dojat, Florence Forbes, Catherine Garbay and Anna K. Prohl. Their work appears in journals such as IEEE Transactions on Medical Imaging, NeuroImage, Magnetic Resonance in Medicine, Neurology and Cerebral Cortex.

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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