Rémy Guillevin

6.1k total citations · 1 hit paper
108 papers, 3.9k citations indexed

About

Rémy Guillevin is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Molecular Biology. According to data from OpenAlex, Rémy Guillevin has authored 108 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Radiology, Nuclear Medicine and Imaging, 31 papers in Genetics and 23 papers in Molecular Biology. Recurrent topics in Rémy Guillevin's work include Glioma Diagnosis and Treatment (29 papers), Advanced MRI Techniques and Applications (15 papers) and Radiomics and Machine Learning in Medical Imaging (13 papers). Rémy Guillevin is often cited by papers focused on Glioma Diagnosis and Treatment (29 papers), Advanced MRI Techniques and Applications (15 papers) and Radiomics and Machine Learning in Medical Imaging (13 papers). Rémy Guillevin collaborates with scholars based in France, United States and Switzerland. Rémy Guillevin's co-authors include Jean-Noël Vallée, Alexandre Vallée, Yves Lecarpentier, Hugues Duffau, Laurent Capelle, Emmanuel Mandonnet, Khê Hoang‐Xuan, J. Chiras, Karima Mokhtari and Florence Laigle–Donadey and has published in prestigious journals such as Journal of Clinical Oncology, Neurology and Annals of Neurology.

In The Last Decade

Rémy Guillevin

98 papers receiving 3.9k citations

Hit Papers

18F-FDG PET Uptake Characterization Through Texture Analy... 2014 2026 2018 2022 2014 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rémy Guillevin France 33 1.4k 1.3k 887 654 505 108 3.9k
Philip C. De Witt Hamer Netherlands 36 1.8k 1.3× 1.4k 1.1× 1.1k 1.3× 561 0.9× 760 1.5× 117 4.9k
Sandeep Mittal United States 39 1.1k 0.8× 1.3k 1.0× 1.1k 1.2× 641 1.0× 741 1.5× 147 5.6k
Sumei Wang China 34 647 0.4× 1.2k 0.9× 1.2k 1.3× 384 0.6× 305 0.6× 159 4.3k
Christian Senft Germany 36 2.3k 1.6× 953 0.7× 762 0.9× 747 1.1× 1.3k 2.6× 171 4.8k
Quan Jiang United States 37 646 0.4× 1.2k 0.9× 1.2k 1.4× 471 0.7× 1.1k 2.2× 135 4.7k
Peter M. Black United States 33 1.3k 0.9× 546 0.4× 1.6k 1.8× 484 0.7× 395 0.8× 70 4.2k
Johan Pallud France 38 2.6k 1.8× 1.3k 1.0× 526 0.6× 727 1.1× 1.2k 2.4× 178 4.7k
Nathalie L. Albert Germany 32 2.1k 1.5× 2.1k 1.6× 350 0.4× 739 1.1× 707 1.4× 158 4.0k
Satoshi O. Suzuki Japan 41 1.4k 1.0× 1.2k 1.0× 2.4k 2.7× 437 0.7× 726 1.4× 206 7.0k
Thomas Czech Austria 44 1.5k 1.0× 463 0.4× 1.6k 1.8× 624 1.0× 679 1.3× 209 6.0k

Countries citing papers authored by Rémy Guillevin

Since Specialization
Citations

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

Fields of papers citing papers by Rémy Guillevin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rémy Guillevin

This figure shows the co-authorship network connecting the top 25 collaborators of Rémy Guillevin. A scholar is included among the top collaborators of Rémy Guillevin 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 Rémy Guillevin. Rémy Guillevin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bourdon, Pascal, et al.. (2023). A complete pipeline for glioma grading using intelligible AI on multimodal MRI data. Medical Research Archives. 11(5).
4.
Urruty, Thierry, et al.. (2022). A multi-sequences MRI deep framework study applied to glioma classfication. Multimedia Tools and Applications. 81(10). 13563–13591. 15 indexed citations
5.
Bourdon, Pascal, Claire Boutet, Jean‐Philippe Cottier, et al.. (2021). Exploring Radiologic Criteria for Glioma Grade Classification on the BraTS Dataset. IRBM. 42(6). 407–414. 30 indexed citations
6.
Huy, Quang, et al.. (2021). 7T MRI super-resolution with Generative Adversarial Network. Electronic Imaging. 33(18). 106–1. 7 indexed citations
7.
Bourdon, Pascal, et al.. (2020). Learning a CNN on multiple sclerosis lesion segmentation with self-supervision. Electronic Imaging. 32(17). 3–1. 4 indexed citations
8.
Vallée, Alexandre, Yves Lecarpentier, Rémy Guillevin, & Jean-Noël Vallée. (2018). Demyelination in Multiple Sclerosis: Reprogramming Energy Metabolism and Potential PPARγ Agonist Treatment Approaches. International Journal of Molecular Sciences. 19(4). 1212–1212. 49 indexed citations
9.
Vallée, Alexandre, Yves Lecarpentier, Rémy Guillevin, & Jean-Noël Vallée. (2017). Interactions between TGF-β1, canonical WNT/β-catenin pathway and PPAR γ in radiation-induced fibrosis. Oncotarget. 8(52). 90579–90604. 158 indexed citations
10.
Vallée, Alexandre, Yves Lecarpentier, Rémy Guillevin, & Jean-Noël Vallée. (2017). Reprogramming energetic metabolism in Alzheimer's disease. Life Sciences. 193. 141–152. 32 indexed citations
11.
Vallée, Alexandre, Yves Lecarpentier, Rémy Guillevin, & Jean-Noël Vallée. (2017). PPARγ agonists: Potential treatments for exudative age-related macular degeneration. Life Sciences. 188. 123–130. 24 indexed citations
12.
Jaafari, Nématollah, et al.. (2017). 1 H magnetic resonance spectroscopy suggests neural membrane alteration in specific regions involved in obsessive-compulsive disorder. Psychiatry Research Neuroimaging. 269. 48–53. 11 indexed citations
13.
Lefort, Muriel, et al.. (2014). An efficient strategy based on an individualized selection of registration methods. Application to the coregistration of MR and SPECT images in neuro-oncology. Physics in Medicine and Biology. 59(22). 6997–7011. 2 indexed citations
14.
Houillier, Caroline, Gentian Kaloshi, Karima Mokhtari, et al.. (2010). IDH1 or IDH2 mutations predict longer survival and response to temozolomide in low-grade gliomas. Neurology. 75(17). 1560–1566. 402 indexed citations
15.
Pallud, Johan, Hayat Belaïd, Rémy Guillevin, Jean-Noël Vallée, & Laurent Capelle. (2009). Management of associated glioma and arteriovenous malformation – the priority is the glioma. British Journal of Neurosurgery. 23(2). 197–198. 8 indexed citations
16.
Béhin, Anthony, et al.. (2009). Syndrome de Bing-Neel révélateur d’une maladie de Waldenström : étude d’un cas et revue de la littérature. Revue Neurologique. 166(1). 66–75. 8 indexed citations
17.
Martin–Duverneuil, N., Ahmed Idbaïh, Khê Hoang‐Xuan, et al.. (2006). MRI features of neurodegenerative Langerhans cell histiocytosis. European Radiology. 16(9). 2074–2082. 60 indexed citations
18.
Vallée, Jean-Noël, Laurent Pierot, Francisco Mont’Alverne, et al.. (2005). Unruptured intracranial aneurysms treated by three-dimensional coil embolization: evaluation of the postoperative aneurysm occlusion volume. Neuroradiology. 47(6). 438–445. 20 indexed citations
19.
Jbabdi, Saâd, Emmanuel Mandonnet, Hugues Duffau, et al.. (2005). Simulation of anisotropic growth of low‐grade gliomas using diffusion tensor imaging. Magnetic Resonance in Medicine. 54(3). 616–624. 206 indexed citations
20.
Vallée, Julie, Sophie Crozier, Rémy Guillevin, et al.. (2003). Acute basilar artery occlusion treated by thromboaspiration in a cocaine and ecstasy abuser. Neurology. 61(6). 839–841. 19 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026