LE GUYADER Carole

  02 32 95 99 14

  • Research topics/Thèmes de recherche: Méthodes hybrides Variationnelles/DL sous contraintes topologiques et/ou géométriques. PDE, Analysis and numerical simulation, Image and signal processing, biomedical imaging, HPC & Applications (medicine, geophysics...).
  • Ph. D. supervision/encadrement doctoral: Alexandre Leclerc (2023-..., with C. Gout et P. Besset, CIFRE Buawei), Zoé Lambert (2019-2022, co-supervision with C. Petitjean), Noémie Debroux (de nov. 2015 à 2018). Solène Ozeré de 2012 à 2015 (co supervision 75%), Ratiba Derfoul, du 2010 au 4/10/2013 (co supervision 50%).
  • Collaborations: UC Los Angeles (USA), Cambridge University (GB), Paris Dauphine, Université de Pau, Université de Lille.
  • Industrial links/Liens industriels: Siemens-Gamesa (depuis 2019), Dassault Systèmes, 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: Correspondante LMI du GDR MIA depuis 2021, Responsable des enseignements en Mathématiques du département STPI INSA Rouen depuis 2019, Directrice adjointe du département GM 2018/2020. 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 depuis, 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.
  • Correspondante INSA du projet ANR MEDISEG (2022-...)
  • 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).
  • Membre du projet M2SiNum (Région Normandie et Europe, 2018-2021)
  • Pilote des équipes INSA au Hackathon GENCI/CRIANN depuis 2017.
    2019 : Une équipe GM5 encadrée par C. Le Guyader et P. Bousquet-Melou au Hackathon GENCI (lien)
    2017 : Hackathon 2017 - Equipe INSA Rouen GM

Le LMI affiché à l'Institut Henri Poincaré :
Success story : e@lin [Fiche Labex AMIES et Fondation Sciences Mathématiques de Paris]

Main publications (since 2006)

  • C. Le Guyader et Z. Lambert, About the Incorporation of Topological Prescriptions in CNNs for Medical Image Semantic Segmentation, Journal of Mathematical Imaging and Vision 66(4), pp. 419–446, 2024.
  • C. Le Guyader, S. Ainouz, S. Canu, A Physically Admissible Stokes Vector Reconstruction in Linear Polarimetric Imaging. J. Math. Imaging Vis. 65(4): 592-617, 2023.
  • N. Debroux, C. Le Guyader, Asymptotic Result for a Decoupled Nonlinear Elasticity-Based Multiscale Registration Model. SSVM 2023: 639-651, 2022.
  • Z. Lambert, C. Le Guyader, C. Petitjean, Enforcing Geometrical Priors in Deep Networks for Semantic Segmentation Applied to Radiotherapy Planning. J. Math. Imaging Vis. 64(8): 892-915, 2022.
  • N. Debroux, C. Le Guyader, L. A. Vese, A Multiscale Deformation Representation. SIAM J. Imaging Sci. 16(2): 802-841, 2023.
  • Z. Lambert, C. Le Guyader, C. Petitjean, On the Inclusion of Topological Requirements in CNNs for Semantic Segmentation Applied to Radiotherapy. SSVM 2023: 363-375, 2022.
  • Z. Lambert, C. Le Guyader, C., Petitjean, Enforcing Geometrical Priors in Deep Networks for Semantic Segmentation Applied to Radiotherapy Planning, Journal of Mathematical Imaging and Vision, 64(8): 892-915, 2022.
  • V. Corona, Aviles-Rivero, A., Debroux, N., Le Guyader, C., Schönlieb, C.-B., Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution, Medical Image Analysis 68, 2021.
  • N. Debroux, Le Guyader, C., Vese, L.A., Multiscale registration, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12679 LNCS, pp. 115-127, 2021.
  • Z. Lambert, Le Guyader, C., Petitjean, C. , Analysis of the weighted Van der Waals-Cahn-Hilliard model for image segmentation, 2020 10th International Conference on Image Processing Theory, Tools and Applications, IPTA 2020
  • N. Debroux, Lienemann, G., Magnin, B., Le Guyader, C., Vacavant, A., A Time-Dependent Joint Segmentation and Registration Model: Application to Longitudinal Registration of Hepatic DCE-MRI Sequences, 10th International Conference on Image Processing Theory, Tools and Applications, IPTA 2020, 2020.
  • N. Debroux, Le Guyader, C., Vese, L.A., A Nonlocal Laplacian-Based Model for Bituminous Surfacing Crack Recovery and its MPI Implementation, Journal of Mathematical Imaging and Vision 62(6-7), pp. 1007-1033, 2020.
  • N. Debroux , J. Aston, F. Bonardi, A. Forbes, C. Le Guyader, M. Romanchikova, and C.-B. Schönlieb, A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis, SIAM J. Imaging Sci., 13(1), 351–380, 2020.
  • Corona, V., Aviles-Rivero, A.I., Debroux, N., Graves, M., Le Guyader, C., Schönlieb, C.-B., Williams, G., Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11603 LNCS, pp. 263-274, 2019.
  • N. Debroux, C. Le Guyader, A joint segmentation/registration model based on a nonlocal characterization of weighted total variation and nonlocal shape descriptors, SIAM Journal on Imaging Sciences (SIIMS), 11(2), pp. 957-990, 2018.
  • N. Debroux, C. Le Guyader, L. Vese, A second order free discontinuity model for bituminous surfacing crack recovery and analysis of a nonlocal version of it,  Annals of Mathematical Sciences and Applications Volume 3 (Special issue in honor of Professor David Mumford, dedicated to the memory of Jennifer Mumford), pp. 49 – 88, 2018.
  • N. Debroux, C. Le Guyader, S. Ozeré, A Non-Local Topology-Preserving Segmentation Guided Registration Model, Journal of Mathematical Imaging and Vision, 59, Issue 3, pp 432–455, 2017.
  • N. Debroux, Le Guyader, C., A unified hyperelastic joint segmentation/registration model based on weighted total variation and nonlocal shape descriptors,  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10302 LNCS, pp. 614-625, 2017.
  • N. Debroux, C. Le Guyader, L. A. Vese, A second order free discontinuity model for bituminous surfacing crack recovery and analysis of a nonlocal version of it, Annals of Mathematical Sciences and Applications, special issue in honor of Professor David Mumford, 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)

  • N. Debroux, and C. Le Guyader, A unified hyperelastic joint segmentation/registration model based on weighted total variation and nonlocal shape descriptors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10302 LNCS, pp. 614-625, 2017.
  • 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

  • Oceanic surface current approximation from sparse data, H. Barucq, M. Chyba, C. Gout and C. Le Guyader, accepted for publication, IEEE IGARSS ref#1525, to appear 2020.
  • Coastline erosion study via UAV drone remote sensing using python modelling electrical resistivity imaging, (PyMERI), R. Antoine, I. Ciotir, S. Costa, Y. Fargier, C. Fauchard,  C. Gout, C. Le Guyader, O. Maquaire, S. Taoum, A. Tonnoir, accepted for publication, IEEE IGARSS ref#1321, to appear 2020.
  • Multi-tasking to Correct : Motion-Compensated MRI via Joint Reconstruction and Registration, Corona V., Aviles-Rivero A., Debroux N., Graves M., Le Guyader C., Schönlieb C., Willians G., accepted in Scale Space and Variational Methods in Computer Vision : 7 th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019.
  • Motion Correction Resolved for MRI via Multi-Tasking : A Simultaneous Reconstruction and Registration Approach, Corona* V., Aviles-Rivero A., Debroux N., Graves M., Le Guyader C., Scönlieb C., Williams G.,  accepted abstract for digital poster at the ISMRM (International Society for Magnetic Resonance in Medicine) 27th Annual Meeting & Exhibition, Montreal, Canada, May 11-16, 2019.
  • 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.