Accès direct au contenu


Version anglaise


Accueil > Formations > Master MVA > Présentation des cours

Deformable models and geodesic methods for image analysis

Lecturer : Laurent COHEN and Gabriel PEYRE, (CNRS et Université Paris-Dauphine PSL

Cours en anglais sauf si tous les étudiants sont francophones.

Objective of the course :

A large overview of methods and algorithms of deformable models for image segmentation, illustrated by concrete applications

Topics :

  • Variational Methods and Partial Differential Equations
  • Numerical Methods, Algorithmics, and Industrial applications

  • Curve and Surface Segmentation by Elastic Deformable Models, Active Contours, Deformable Surfaces, Balloon Model

  • Finite Differences, finite elements, level sets, front competition

  • Active Region, Shape Prior

  • Minimal Paths and Geodesics

  • Eikonal Equation, front propagation and Fast Marching

  • Various metrics: 2D, 3D, surface, anisotropic, space+radius

  • Geodesic remeshing of domains and surfaces

  • Applications: surface segmentation, vessel segmentation, virtual endoscopy, extraction of tubular and tree structure...

  • Testing and implementation of algorithms in Matlab

Prerequisites :

Admission to MVA sufficient

Organization of courses :

  • About half on deformable models and half on geodesic methods.

  • 9 sessions of 3 hours, including 3 with 2 hours lab

Validation :


    References :

    -      Finite element methods for active contour models and balloons for 2D and 3D images. Laurent D. Cohen and Isaac Cohen. IEEE Trans. on PAMI-15(11), November 1993.

    -       Minimal Paths and Fast Marching Methods for Image Analysis. , Laurent D. Cohen, In Mathematical Models in Computer Vision: The Handbook, Springer 2005.

    -       Geodesic Methods in Computer Vision and Graphics, Gabriel Peyré, Mickaël Péchaud, Renaud Keriven and Laurent D. Cohen, Foundations and Trends in Computer Graphics and Vision 5, 3-4 (2010) 197-397 (book of 200 pages).

    -       Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement. F. Benmansour and L. D. Cohen, In IJCV, April 2011, Volume 92, Number 2, Pages 192-210     

    More information...