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  • Research topics/Thèmes de recherche: PDE, Analysis and numerical simulation, Image and signal processing, biomedical imaging, HPC & Applications (medicine, geophysics...).
  • Ph. D. supervision/encadrement doctoral: Martin Pierre Schmidt (with  C. Gout, since march 2017), Noémie Debroux (since nov. 2015). Solène Ozeré Dr depuis le 6/11/2015  (thesis duration : 3 y et 2 days, co supervision 75%), Ratiba Derfoul, Dr since  4/10/2013 (thesis duration: 3 y et 4d, co supervision 50%).
  • Collaborations: UC Los Angeles (USA), Cambridge University (GB), Paris Dauphine, Université de Pau, Université de Lille
  • Industrial links/Liens industriels: IFP Energies Nouvelles (2010-2013), ENGIE/GdF SUEZ/LCV.
  • Teaching/Enseignement: Génie Mathématique (PDE, CAGD in M1 level Variatioanl methods in image processing in M2) and L1/L2 (STPI - course in English).
  • Administrative activites/Activités Administratives: Assistante de prévention du LMI/GM depuis 2017. Membre du Comité de liaison du GT SMAI-SIGMA depuis 2015. Membre du Comité Editorial de Matapli (SMAI) de 2008 à 2014. Elue au CA de l'INSA Rouen jusqu'en 2005. Directrice des Etudes GM4, Dpt Génie Mathématique depuis 2013.
  • Habilitation à Diriger des Recherches : soutenue le 16/11/2012 à Rouen. Titre :Contribution à l'analyse mathématique d'images: segmentation, registration et décomposition
    Jury: Grégoire ALLAIRE, Ecole Polytechnique (Rapporteur), M. Christian GOUT,  INSA Rouen,M. Olivier LEY, INSA Rennes (Rapporteur),M. Simon MASNOU, Université Lyon 1 (Rapporteur), Mme. Valérie PERRIER, INPG-ENSIMAG (Présidente du jury), M. Gabriel PEYRE, Université Paris-Dauphine.
  • 2005/2009 : Assistant Prof./MCF à l'INSA de Rennes (IRMAR - UMR 6625, Rennes, 2005-2009) puis INSA Rouen.
  • Pilotage du projet du LMI "Imagerie Mathématique et Analyse Numérique" au  CRIHAN depuis 2013.
  • Pilotage du projet du LMI "Modélisation, approximation et visualisation d’un champ de vent à partir de données ponctuelles: applications à l’éolien" (@Olin pour EOlien LMI INSA) auprès du LABEX AMIES  en relation avec GDF SUEZ/LCV depuis 2014.
  • Co-pilotage du projet M2NUM du GRR LMN - Région Haute Normandie (depuis 2014).

2017  Ph. D. proposal :
Image segmentation and observer strategy for elastography

Ph. D. supervisor : C. Le Guyader
(avec A. Tonnoir, collaboration with INRIA M3DISIM Paris Saclay (P. Moireau))


Main publications (since 2006)

International journals :

  • N. Debroux, C. Le Guyader, S. Ozeré,  A Non-Local Topology-Preserving Segmentation Guided Registration Model, Journal of Mathematical Imaging and Vision, in press, to appear 2017.
  • S. Ozeré, C. Le Guyader, C. Gout, Joint segmentation/registration model by shape alignment via weighted total variation minimization and nonlinear elasticity, SIAM J. on Imaging Sciences 8(3), 1981–2020,  2015.
  • C. Le Guyader, S. Ozeré, Topology preservation for image-registration-related deformation fields, Communications in Math. Sciences 13 (2015), no. 5, 1135–1161..
  • R. Derfoul et C. Le Guyader, A relaxed problem of registration based on the saint Venant-kirchhoff material stored energy for the mapping of mouse brain gene expression data to a neuroanatomical mouse atlas, SIAM J. on Imaging Sciences 7 (4) pp. 2175-2195, 2014.
  • Schaeffer, Hayden; Duggan, Nóirín; le Guyader, Carole; Vese, Luminita Topology preserving active contours. Commun. Math. Sci. 12 (2014), no. 7, 1329–1342.
  • C. Le Guyader, D. Apprato, C. Gout, Spline approximation of gradient fields: applications to wind velocity fields, Mathematics and Computers in Simulation 97, pp. 260–279, 2014.
  • R. Derfoul, S. Da Veiga, C. Gout, C. Le Guyader, E. Tillier , Image processing tools for better incorporation of 4D seismic data, into reservoir models, J. of Comp. and Applied Math. 240 , pp. 111-122, 2013.
  • Bonamy, C., Le Guyader, C., Split Bregman iteration and infinity Laplacian for image decomposition, Journal of Computational and Applied Mathematics 240 pp. 99-110, 2013.
  • C. Le Guyader, C. Gout, A.S. Macé, D. Apprato. Gradient fields approximation: application to registration processes in image processing, J. of Comp. and Applied Math. 240 , pp. 135-147, 2013.
  • Tungyou Lin, Carole Le Guyader, Ivo D. Dinov, Paul M. Thompson, Arthur W. Toga, Luminita A. Vese: Gene Expression Data to Mouse Atlas Registration Using a Nonlinear Elasticity Smoother and Landmark Points Constraints. J. Sci. Comput. 50(3): 586-609 (2012)
  • C. Le Guyader, D. Apprato, C. Gout, Construction of Topology-Preserving Deformation Fields. IEEE Trans. on Image Processing,21 (4) , art. no. 6093964 , pp. 1587-1599, 2012.
  • N. Forcadel, et C.  Le Guyader, A short time existence/uniqueness result for a nonlocal topology-preserving segmentation model,  Journal of Differential Equations 253 (3) , pp. 977-995, 2012.
  • Carole Le Guyader, Luminita A. Vese: A combined segmentation and registration framework with a nonlinear elasticity smoother. Computer Vision and Image Understanding 115(12): 1689-1709 (2011)
  • C. Le Guyader and L. Guillot, Extrapolation of vector fields using the infinity Laplacian and with applications to image segmentation, Communications in Mathematical Sciences, 7(2) : 423-452, 2009.
  • C. Le Guyader and L. Vese, Self-Repelling Snakes for topology-preserving segmentation models, IEEE Transactions on Image Processing, 17(5) :767-779, 2008.
  • C. Le Guyader and C. Gout, Geodesic Active Contour under Geometrical Conditions : Theory and 3D applications, Numerical Algorithms, 48(1-3) :105-133, 2008.
  • C. Gout, C. Le Guyader, L. Romani and A.-G. Saint-Guirons, Approximation of Surfaces with fault(s) and/or rapidly varying data, using a segmentation process, Dm splines and the finite element method, Numerical Algorithms, 48(1-3) : 67-92, 2008.
  • N. Forcadel, C. Le Guyader and C. Gout, Generalized Fast Marching Method : Applications to Image Segmentation, Numerical Algorithms, 48(1-3) :189-211, 2008.
  • C. Gout and C. Le Guyader, Segmentation of complex geophysical structures with well data, Comput. Geosci, 10 : 361-372, 2006

Variational Methods in Image Processing presents the principles, techniques, and applications of variational image processing. The text focuses on variational models, their corresponding Euler–Lagrange equations, and numerical implementations for image processing. It balances traditional computational models with more modern techniques that solve the latest challenges introduced by new image acquisition devices.
The book addresses the most important problems in image processing along with other related problems and applications. Each chapter presents the problem, discusses its mathematical formulation as a minimization problem, analyzes its mathematical well-posedness, derives the associated Euler–Lagrange equations, describes the numerical approximations and algorithms, explains several numerical results, and includes a list of exercises. MATLAB® codes are available online.
Filled with tables, illustrations, and algorithms, this self-contained textbook is primarily for advanced undergraduate and graduate students in applied mathematics, scientific computing, medical imaging, computer vision, computer science, and engineering. It also offers a detailed overview of the relevant variational models for engineers, professionals from academia, and those in the image processing industry. 

<https://www.crcpress.com/Variational-Methods-in-Image-Processing/Vese-Le-Guyader/9781439849736>

Book (chapter)

  • D. Apprato, C. Gout and C. Le Guyader, Surface approximation from rapidly varying data : applications to geophysical surfaces and seafloor surfaces, Geoscience and Remote Sensing, Chapter 17, InTech Editor Croatia, ISBN 978-953-307-0032, 347-374, 2009.

Proceedings/International conferences

  • Debroux, Noemie, le Guyader Carole, A Unified Hyperelastic Joint Segmentation/registration Model Based on Weighted Total Variation and Piecewise Constant Mumford-Shah Model, 2017 IEEE International Symposium on Biomedical Imaging, April 18-21, 2017, Melbourne Convention and Exhibition Centre, Australia.
  • *R. Fontanges, C. Gout, N. Forcadel, C. Le Guyader, A. Zakharova, T. Roy, D. Apprato, P. Alexandre, B. Jobard, Wind velocity field approximation from sparse data for new wind farm installation, 19th European Conference for Industry - ECMI conference, Santiago de Compostela, 13-17 juin 2016, Espagne. (http://www.usc.es/congresos/ecmi2016/wp-content/uploads/2016/05/282.pdf)
  • C. Le Guyader, *N. Debroux, INSA Rouen, C.-B. Schönlieb, University of Cambridge, and L.A. Vese, University of California, A Unified Hyperelastic Joint Segmentation/registration Model Based on Weighted Total Variation and Nonlocal Shape Descriptors, Los Angeles, SIAM conference on Imaging Science, Albuquerque, USA, May 23-26, 2016.
  • S. Ozeré, C. Le Guyader, Nonlocal Joint Segmentation Registration Model, accepté pour publication dans "Fifth International Conference on Scale Space and Variational Methods in Computer Vision", Lège Cap Ferret, France, 2015.
  • C. Le Guyader, S. Ozeré, A joint Segmentation-Registration framework based on Weighted Total Variation and Nonlinear Elasticity Principle, IEEE ICIP, to appear 2015.
  • D. Apprato, C. Gout, C. Le Guyader, On the construction of topology-preserving deformations, , Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8314 , art. no. 83141Q, 2012.
  • Lin, T. ; Lee, E.-F. ; Dinov, I. ; Le Guyader, C. ; Thompson, P. ; Toga, A.W. ; Vese, L.A. ; A landmark-based nonlinear elasticity model for mouse atlas registration; Fifth IEEE International Symposium on Biomedical Imaging : From Nano to Macro (ISBI) ; pp 788-791 ; May 2008 .
  • Yanovsky, I., Le Guyader, C., Leow, A., Thompson, P. and Vese, L., Nonlinear Elastic Registration with Unbiased Regularization in Three Dimensions, id. 220, pp 56-67, MIDAS Journal, 2008.
  • Yanovsky, I.., Le Guyader, C., Leow, A., Toga, A., Thompson,P. and Vese, L., Unbiased Volumetric Registration via Nonlinear Elastic Regularization,  Mathematical Foundations of Computational Anatomy, 1–8, 2008.
  • T. Lin, C. Le Guyader, E.-F. Lee, I. Dinov, P. M. Thompson, A. W. Toga  and L. A. Vese, Gene to mouse atlas registration using a landmark-based nonlinear elasticity smoother, Medical Imaging 2009 : Image Processing. Proc. of SPIE Vol. 7259, 72592Q, 2009.
  • L. Guillot and C. Le Guyader, Extrapolation of Vector Fields Using the Infinity Laplacian and with Applications to Image Segmentation, X.-C. Tai et al. (Eds); SSVM 2009, LNCS 5567, pp 87-99, 2009, Springer-Verlag.
  • C. Le Guyader and L. Vese, A combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother, X.-C. Tai et al. (Eds); SSVM 2009, LNCS 5567, pp 600-611, 2009, Springer-Verlag.
  • D. Apprato; C. Gout; C. Le Guyader; On the construction of topology-preserving deformations, Medical Imaging 2012, SPIE Volume: 8314, Editor(s): David R. Haynor; Sébastien Ourselin, ISBN: 9780819489630.