Empenn

9.7k citations
378 papers ·

Impact in

Papers in

Empenn

306 papers receiving 8.3k citations

Peers

Empenn
Comparison fields: 5 of 192
  • Radiology, Nuclear Medicine and Imaging 2.9k
  • Computer Vision and Pattern Recognition 2.2k
  • Cognitive Neuroscience 1.7k
  • Neurology 625
  • Computational Mathematics 41
Replace ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologique with:
ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologique France
Bristol General Hospital United Kingdom
Philips (Spain) Spain
Siemens (Switzerland) Switzerland
General Electric (France) France
Université Paris-Seine France
Digital Catapult United Kingdom
The Neurosciences Foundation United Kingdom
NIHR Queen Square Dementia Biomedical Research Unit United Kingdom
Imagerie par Résonance Magnétique Médicale et Multi-Modalités France
Empenn relative to ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologique France ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologique's profile →
Citations per field
00.5×2×3×4.1×
ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologique · 1×
Citations per year

Countries citing scholars working at Empenn

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Empenn. 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 papers produced at Empenn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Empenn more than expected).

Fields of papers published by authors at Empenn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Empenn at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Empenn at the time of their publication.

About Empenn

In recent decades, authors affiliated with Empenn have published 378 papers, which have received a total of 9.7k indexed citations . Scholars at this organization have produced 121 papers in Radiology, Nuclear Medicine and Imaging, 71 papers in Cognitive Neuroscience, 2 papers in Computational Mathematics, 64 papers in Computer Vision and Pattern Recognition and 29 papers in Neurology on the topics of Advanced MRI Techniques and Applications (67 papers), Advanced Neuroimaging Techniques and Applications (65 papers), Functional Brain Connectivity Studies (45 papers), Medical Image Segmentation Techniques (42 papers), Multiple Sclerosis Research Studies (26 papers), EEG and Brain-Computer Interfaces (20 papers), MRI in cancer diagnosis (18 papers) and Biomedical Text Mining and Ontologies (14 papers). Their work is cited by papers focused on Radiology, Nuclear Medicine and Imaging (2.9k citations), Computer Vision and Pattern Recognition (2.2k citations), Cognitive Neuroscience (1.7k citations), Neurology (625 citations) and Computational Mathematics (41 citations). Authors at Empenn collaborate with scholars in France, United States and Canada and have published in prestigious journals including NeuroImage, Annals of Physical and Rehabilitation Medicine, IEEE Transactions on Medical Imaging, PLoS ONE and Journal of Neuroradiology. Some of Empenn's most productive authors include Christian Barillot, Pierre Hellier, D. Louis Collins, Pierre Jannin, Pierrick Coupé, Sylvain Prima, Olivier Commowick, Jean‐Christophe Ferré, Xavier Morandi and Nicolas Wiest-Daesslé.

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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