Loïc Le Folgoc

5.0k total citations
10 papers, 166 citations indexed

About

Loïc Le Folgoc is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Loïc Le Folgoc has authored 10 papers receiving a total of 166 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Computer Vision and Pattern Recognition and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Loïc Le Folgoc's work include Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Image Segmentation Techniques (5 papers) and AI in cancer detection (2 papers). Loïc Le Folgoc is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Image Segmentation Techniques (5 papers) and AI in cancer detection (2 papers). Loïc Le Folgoc collaborates with scholars based in United Kingdom, France and United States. Loïc Le Folgoc's co-authors include Ben Glocker, Antonio Criminisi, Bernhard Kainz, Konstantinos Kamnitsas, Ozan Oktay, Ghislain Vaillant, Yuanwei Li, Daniel Rueckert, Amir Alansary and Benjamin Hou and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Physics in Medicine and Biology and Medical Image Analysis.

In The Last Decade

Loïc Le Folgoc

8 papers receiving 166 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Loïc Le Folgoc 73 64 40 39 18 10 166
Keno März 51 0.7× 37 0.6× 55 1.4× 34 0.9× 75 4.2× 15 182
Rupert Brooks 119 1.6× 113 1.8× 67 1.7× 72 1.8× 38 2.1× 23 282
Florin‐Cristian Ghesu 127 1.7× 48 0.8× 68 1.7× 69 1.8× 15 0.8× 4 266
Rafeef Garbi 78 1.1× 61 1.0× 63 1.6× 28 0.7× 64 3.6× 14 182
Ghislain Vaillant 256 3.5× 55 0.9× 67 1.7× 26 0.7× 20 1.1× 7 339
Jun Xia 194 2.7× 100 1.6× 60 1.5× 37 0.9× 15 0.8× 22 295
Amir Alansary 119 1.6× 121 1.9× 59 1.5× 80 2.1× 27 1.5× 17 319
Mehran Pesteie 108 1.5× 43 0.7× 79 2.0× 67 1.7× 45 2.5× 15 251
Raphaël Prevost 119 1.6× 123 1.9× 97 2.4× 39 1.0× 21 1.2× 14 228
Andrés Anaya-Isaza 102 1.4× 77 1.2× 34 0.8× 82 2.1× 11 0.6× 9 256

Countries citing papers authored by Loïc Le Folgoc

Since Specialization
Citations

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

Fields of papers citing papers by Loïc Le Folgoc

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Loïc Le Folgoc. 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 Loïc Le Folgoc. The network helps show where Loïc Le Folgoc may publish in the future.

Co-authorship network of co-authors of Loïc Le Folgoc

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

All Works

10 of 10 papers shown
1.
Маммадов, А. И., et al.. (2025). Self-supervision enhances instance-based multiple instance learning methods in digital pathology: a benchmark study. Journal of Medical Imaging. 12(6). 61404–61404.
2.
Ellis, Sam, Arjun Nair, Loïc Le Folgoc, et al.. (2022). Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT. 1(August 2022). 1–36. 5 indexed citations
3.
Glocker, Ben, et al.. (2022). A variational Bayesian method for similarity learning in non-rigid image registration. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 119–128. 7 indexed citations
4.
Ellis, Sam, Arjun Nair, Loïc Le Folgoc, et al.. (2021). Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data. Research Portal (King's College London). 5–9. 4 indexed citations
5.
Alansary, Amir, Ozan Oktay, Yuanwei Li, et al.. (2019). Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Analysis. 53. 156–164. 96 indexed citations
6.
Phillips, Mark H., R. Jena, Aditya Nori, et al.. (2018). Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features. Physics in Medicine and Biology. 63(23). 235002–235002. 22 indexed citations
7.
Folgoc, Loïc Le, Hervé Delingette, Antonio Criminisi, & Nicholas Ayache. (2016). Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements. Medical Image Analysis. 36. 79–97. 8 indexed citations
8.
Folgoc, Loïc Le, Hervé Delingette, Antonio Criminisi, & Nicholas Ayache. (2016). Quantifying Registration Uncertainty With Sparse Bayesian Modelling. IEEE Transactions on Medical Imaging. 36(2). 607–617. 19 indexed citations
9.
Margeta, Ján, Loïc Le Folgoc, Yuki Komatsu, et al.. (2015). Local late gadolinium enhancement features to identify the electrophysiological substrate of post-infarction ventricular tachycardia: a machine learning approach. Journal of Cardiovascular Magnetic Resonance. 17. P234–P234.
10.
Folgoc, Loïc Le, Hervé Delingette, Antonio Criminisi, & Nicholas Ayache. (2014). Sparse Bayesian Registration. Lecture notes in computer science. 17(Pt 1). 235–242. 5 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.

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