Frédéric Richard

605 total citations
29 papers, 323 citations indexed

About

Frédéric Richard is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Frédéric Richard has authored 29 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 8 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Artificial Intelligence. Recurrent topics in Frédéric Richard's work include Medical Image Segmentation Techniques (16 papers), Medical Imaging Techniques and Applications (6 papers) and AI in cancer detection (6 papers). Frédéric Richard is often cited by papers focused on Medical Image Segmentation Techniques (16 papers), Medical Imaging Techniques and Applications (6 papers) and AI in cancer detection (6 papers). Frédéric Richard collaborates with scholars based in France, Algeria and United States. Frédéric Richard's co-authors include Hermine Biermé, Laurent D. Cohen, Joan Glaunès, Françoise Tilotta, Yves Rozenholc, Maxime Bérar, Éric Guedj, Agnès Desolneux, Predrag R. Bakić and Andrew D. A. Maidment and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging and Sensors.

In The Last Decade

Frédéric Richard

28 papers receiving 301 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Frédéric Richard France	11	144	70	66	40	31	29	323
Omar Mohd Rijal Malaysia	12	79 0.5×	180 2.6×	80 1.2×	3 0.1×	26 0.8×	53	369
Fuli Wu China	11	71 0.5×	78 1.1×	47 0.7×	16 0.4×	82 2.6×	36	394
Edgard Nyssen Belgium	9	187 1.3×	80 1.1×	66 1.0×	4 0.1×	52 1.7×	41	281
Farhad Ghazvinian Zanjani Netherlands	9	149 1.0×	147 2.1×	185 2.8×	4 0.1×	54 1.7×	17	353
Yuchen Xie China	12	109 0.8×	497 7.1×	79 1.2×	4 0.1×	60 1.9×	26	748
David D. Pokrajac United States	9	76 0.5×	136 1.9×	111 1.7×	6 0.1×	54 1.7×	47	304
Gabriel Efrain Humpire Mamani Netherlands	5	141 1.0×	86 1.2×	78 1.2×	5 0.1×	47 1.5×	6	282
Jinglong Du China	12	262 1.8×	114 1.6×	83 1.3×	7 0.2×	40 1.3×	39	433
Christian Daul France	12	201 1.4×	105 1.5×	71 1.1×	13 0.3×	75 2.4×	62	461
Nripendra Kumar Singh India	3	63 0.4×	60 0.9×	78 1.2×	5 0.1×	47 1.5×	4	210

Countries citing papers authored by Frédéric Richard

Since Specialization

Citations

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

Fields of papers citing papers by Frédéric Richard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frédéric Richard

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

All Works

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20 of 20 papers shown

Richard, Frédéric, et al.. (2024). Full inference for the anisotropic fractional Brownian field. Theory of Probability and Mathematical Statistics. 110(0). 13–29.

Richard, Frédéric, et al.. (2022). FDG-PET to T1 Weighted MRI Translation with 3D Elicit Generative Adversarial Network (E-GAN). Sensors. 22(12). 4640–4640. 10 indexed citations

Richard, Frédéric. (2022). PyAFBF: a Python library for sampling image texturesfrom the anisotropic fractional Brownian field.. The Journal of Open Source Software. 7(75). 3821–3821. 1 indexed citations

Chaux, Caroline, et al.. (2020). An adapted linear discriminant analysis with variable selection for the classification in high-dimension, and an application to medical data. Computational Statistics & Data Analysis. 152. 107031–107031. 19 indexed citations

Richard, Frédéric. (2015). Analysis of Anisotropic Brownian Textures and Application to Lesion Detection in Mammograms. Procedia Environmental Sciences. 27. 16–20. 7 indexed citations

Allassonnière, Stéphanie, et al.. (2013). Statistical models for deformable templates in image and shape analysis. Annales mathématiques Blaise Pascal. 20(1). 1–35. 4 indexed citations

Desolneux, Agnès, et al.. (2012). Bayesian Technique for Image Classifying Registration. IEEE Transactions on Image Processing. 21(9). 4080–4091. 14 indexed citations

Bézière, Nicolas, Christophe Decroos, Frédéric Richard, et al.. (2012). First Combined in Vivo X-Ray Tomography and High-Resolution Molecular Electron Paramagnetic Resonance (EPR) Imaging of the Mouse Knee Joint Taking into Account the Disappearance Kinetics of the EPR Probe. Molecular Imaging. 11(3). 220–8. 10 indexed citations

Tilotta, Françoise, Joan Glaunès, Frédéric Richard, & Yves Rozenholc. (2010). A local technique based on vectorized surfaces for craniofacial reconstruction. Forensic Science International. 200(1-3). 50–59. 19 indexed citations

10.

Desolneux, Agnès, et al.. (2009). A classifying registration technique for the estimation of enhancement curves of DCE-CT scan sequences. Medical Image Analysis. 14(2). 185–194. 4 indexed citations

11.

Tilotta, Françoise, et al.. (2009). Construction and analysis of a head CT-scan database for craniofacial reconstruction. Forensic Science International. 191(1-3). 112.e1–112.e12. 57 indexed citations

12.

Richard, Frédéric & Hermine Biermé. (2009). Statistical Tests of Anisotropy for Fractional Brownian Textures. Application to Full-field Digital Mammography. Journal of Mathematical Imaging and Vision. 36(3). 227–240. 22 indexed citations

13.

Biermé, Hermine, et al.. (2009). Anisotropic texture modeling and applications to medical image analysis. ESAIM Proceedings. 26. 100–122. 3 indexed citations

14.

Richard, Frédéric, et al.. (2008). A SAEM algorithm for the estimation of template and deformation parameters in medical image sequences. Statistics and Computing. 19(4). 465–478. 12 indexed citations

15.

Richard, Frédéric & Hermine Biermé. (2007). A statistical methodology for testing the anisotropy of Brownian textures with an application to full-field digital mammography. 3 indexed citations

16.

Richard, Frédéric, Predrag R. Bakić, & Andrew D. A. Maidment. (2006). Mammogram registration: a phantom-based evaluation of compressed Breast Thickness variation effects. IEEE Transactions on Medical Imaging. 25(2). 188–197. 19 indexed citations

17.

Richard, Frédéric. (2005). A comparative study of markovian and variational image-matching techniques in application to mammograms. Pattern Recognition Letters. 26(12). 1819–1829. 4 indexed citations

18.

Richard, Frédéric & Laurent D. Cohen. (2003). A new Image Registration technique with free boundary constraints: application to mammography. Computer Vision and Image Understanding. 89(2-3). 166–196. 37 indexed citations

19.

Richard, Frédéric. (2002). Résolution de problèmes hyperélastiques de recalage d'images. Comptes Rendus Mathématique. 335(3). 295–299. 1 indexed citations

20.

Richard, Frédéric. (1987). Graphical Analysis of Complex O.D.E. Solutions. Computer Graphics Forum. 6(4). 335–341. 2 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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