2008 |
44 | EE | Vincent Noblet,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
Symmetric Nonrigid Image Registration: Application to Average Brain Templates Construction.
MICCAI (2) 2008: 897-904 |
43 | EE | Vincent Noblet,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
Accurate Inversion of 3-D Transformation Fields.
IEEE Transactions on Image Processing 17(10): 1963-1968 (2008) |
2007 |
42 | EE | Matthieu Brucher,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
Unsupervised Nonlinear Manifold Learning.
ICIP (2) 2007: 109-112 |
41 | EE | Torbjørn Vik,
Fabrice Heitz,
Pierre Charbonnier:
Robust Pose Estimation and Recognition Using Non-Gaussian Modeling of Appearance Subspaces.
IEEE Trans. Pattern Anal. Mach. Intell. 29(5): 901-905 (2007) |
2006 |
40 | EE | Alban Foulonneau,
Pierre Charbonnier,
Fabrice Heitz:
Affine-Invariant Multi-reference Shape Priors for Active Contours.
ECCV (2) 2006: 601-613 |
39 | EE | Alban Foulonneau,
Pierre Charbonnier,
Fabrice Heitz:
Affine-Invariant Geometric Shape Priors for Region-Based Active Contours.
IEEE Trans. Pattern Anal. Mach. Intell. 28(8): 1352-1357 (2006) |
2005 |
38 | EE | Sylvain Faisan,
Laurent Thoraval,
Jean-Paul Armspach,
Marie-Noëlle Metz-Lutz,
Fabrice Heitz:
Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models.
IEEE Trans. Med. Imaging 24(2): 263-276 (2005) |
37 | EE | Vincent Noblet,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
3-D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization.
IEEE Transactions on Image Processing 14(5): 553-566 (2005) |
36 | EE | Michel Salomon,
Fabrice Heitz,
Guy-René Perrin,
Jean-Paul Armspach:
A massively parallel approach to deformable matching of 3D medical images via stochastic differential equations.
Parallel Computing 31(1): 45-71 (2005) |
2004 |
35 | EE | Vincent Noblet,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
A Topology Preserving Non-rigid Registration Method Using a Symmetric Similarity Function-Application to 3-D Brain Images.
ECCV (3) 2004: 546-557 |
34 | EE | Rozenn Dahyot,
Pierre Charbonnier,
Fabrice Heitz:
A Bayesian approach to object detection using probabilistic appearance-based models.
Pattern Anal. Appl. 7(3): 317-332 (2004) |
2003 |
33 | | Torbjørn Vik,
Fabrice Heitz,
Pierre Charbonnier:
Mean shift-based Bayesian image reconstruction into visual subspace.
ICIP (1) 2003: 697-700 |
32 | | Marcel Bosc,
Fabrice Heitz,
Jean-Paul Armspach:
Statistical atlas-based sub-voxel segmentation of 3D brain MRI.
ICIP (2) 2003: 1077-1080 |
31 | | Alban Foulonneau,
Pierre Charbonnier,
Fabrice Heitz:
Geometric shape priors for region-based active contours.
ICIP (3) 2003: 413-416 |
30 | EE | Sylvain Faisan,
Laurent Thoraval,
Jean-Paul Armspach,
Fabrice Heitz:
Unsupervised Learning and Mapping of Brain fMRI Signals Based on Hidden Semi-Markov Event Sequence Models.
MICCAI (2) 2003: 75-82 |
29 | EE | Torbjørn Vik,
Fabrice Heitz,
Jean-Paul Armspach:
Statistical Atlas-Based Detection of Abnormalities in Brain Perfusion: Comparing Models and Estimating Detection Performance.
MICCAI (2) 2003: 838-845 |
28 | EE | Vincent Noblet,
Christian Heinrich,
Fabrice Heitz,
Jean-Paul Armspach:
A Topology Preserving Method for 3-D Non-rigid Brain Image Registration.
MICCAI (2) 2003: 977-978 |
27 | EE | Marcel Bosc,
Torbjørn Vik,
Jean-Paul Armspach,
Fabrice Heitz:
ImLib3D: An Efficient, Open Source, Medical Image Processing Framework in C++.
MICCAI (2) 2003: 981-982 |
26 | EE | Raouf Hamdan,
Fabrice Heitz,
Laurent Thoraval:
A low complexity approximation of probabilistic appearance models.
Pattern Recognition 36(5): 1107-1118 (2003) |
25 | EE | Olivier Musse,
Fabrice Heitz,
Jean-Paul Armspach:
Fast deformable matching of 3D images over multiscale nested subspaces. Application to atlas-based MRI segmentation.
Pattern Recognition 36(8): 1881-1899 (2003) |
2002 |
24 | | Sylvain Faisan,
Laurent Thoraval,
Jean-Paul Armspach,
Fabrice Heitz:
Hidden semi-Markov event sequence models: application to brain functional MRI sequence analysis.
ICIP (1) 2002: 880-883 |
23 | | Michel Salomon,
Guy-René Perrin,
Fabrice Heitz:
Parallel Sampling with Stochastic Differential Equations for 3D Deformable Matching of Medical Images.
PDPTA 2002: 40-48 |
2001 |
22 | EE | Rozenn Dahyot,
Pierre Charbonnier,
Fabrice Heitz:
Unsupervised statistical detection of changing objects in camera-in-motion video.
ICIP (1) 2001: 638-641 |
21 | | Christophoros Nikou,
Fabrice Heitz,
Jean-Paul Armspach:
A Physically-based Statistical Deformable Model for Brain Image Analysis.
IEEE Trans. Med. Imaging 20(10): 1026-1037 (2001) |
20 | EE | Olivier Musse,
Fabrice Heitz,
Jean-Paul Armspach:
Topology preserving deformable image matching using constrained hierarchical parametric models.
IEEE Transactions on Image Processing 10(7): 1081-1093 (2001) |
2000 |
19 | EE | Pierre Charbonnier,
Fabrice Heitz:
Robust Visual Recognition of Color Images Rozenn Dahyot, Pierre.
CVPR 2000: 1685-1690 |
18 | EE | Christophoros Nikou,
Fabrice Heitz,
Jean-Paul Armspach,
Gloria Bueno:
A Physically-Based Statistical Deformable Model for Brain Image Analysis.
ECCV (2) 2000: 528-542 |
17 | | Gloria Bueno,
Christophoros Nikou,
Olivier Musse,
Fabrice Heitz,
Jean-Paul Armspach:
Construction of a 3D Physically-Based Multi-Object Deformable Model.
ICIP 2000 |
16 | | Olivier Musse,
Fabrice Heitz,
Jean-Paul Armspach:
Topology Preserving Deformable Image Matching Using Constrained Hierarchical Parametric Models.
ICIP 2000 |
15 | EE | Vincent Agnus,
Christian Ronse,
Fabrice Heitz:
Spatio-Temporal Segmentation Using 3D Morphological Tools.
ICPR 2000: 3885-3892 |
14 | EE | Jean-Marc Laferté,
Patrick Pérez,
Fabrice Heitz:
Discrete Markov image modeling and inference on the quadtree.
IEEE Transactions on Image Processing 9(3): 390-404 (2000) |
1999 |
13 | EE | Raouf Hamdan,
Fabrice Heitz,
Laurent Thoraval:
Gesture Localization and Recognition using Probabilistic Visual Learning.
CVPR 1999: 2098-2103 |
12 | EE | Olivier Musse,
Fabrice Heitz,
Jean-Paul Armspach:
3D Deformable Image Matching Using Multiscale Minimization of Global Energy Functions.
CVPR 1999: 2478-2484 |
11 | EE | Charles Kervrann,
Fabrice Heitz:
Statistical deformable model-based segmentation of image motion.
IEEE Transactions on Image Processing 8(4): 583-588 (1999) |
10 | EE | Christophoros Nikou,
Fabrice Heitz,
Jean-Paul Armspach:
Robust voxel similarity metrics for the registration of dissimilar single and multimodal images.
Pattern Recognition 32(8): 1351-1368 (1999) |
1998 |
9 | EE | Christophoros Nikou,
Fabrice Heitz,
Jean-Paul Armspach:
Robust Registration of Dissimilar Single and Multimodal Images.
ECCV (2) 1998: 51-65 |
8 | | Christophoros Nikou,
Fabrice Heitz,
Jean-Paul Armspach:
Multimodal Image Registration using Statistically Constrained Deformable Multimodels.
ICIP (1) 1998: 838-842 |
7 | | Charles Kervrann,
Fabrice Heitz:
A Hierarchical Markov Modeling Approach for the Segmentation and Tracking of Deformable Shapes.
Graphical Models and Image Processing 60(3): 173-195 (1998) |
1996 |
6 | | Patrick Pérez,
Fabrice Heitz:
Restriction of a Markov random field on a graph and multiresolution statistical image modeling.
IEEE Transactions on Information Theory 42(1): 180-190 (1996) |
1995 |
5 | EE | Jean-Marc Laferté,
Fabrice Heitz,
Patrick Pérez,
Eric Fabre:
Hierarchical Statistical Models for the Fusion of Multiresolution Image Data.
ICCV 1995: 908-913 |
4 | EE | Charles Kervrann,
Fabrice Heitz:
A Markov random field model-based approach to unsupervised texture segmentation using local and global spatial statistics.
IEEE Transactions on Image Processing 4(6): 856-862 (1995) |
3 | | Étienne Mémin,
Fabrice Heitz,
François Charot:
Efficient Parallel Nonlinear Multigrid Algorithms for Low-Level Vision Applications.
J. Parallel Distrib. Comput. 29(1): 96-103 (1995) |
1994 |
2 | | Charles Kervrann,
Fabrice Heitz:
Robust Tracking of Stochastic Deformable Models in Long Image Sequences.
ICIP (3) 1994: 88-92 |
1993 |
1 | EE | Fabrice Heitz,
Patrick Bouthemy:
Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields.
IEEE Trans. Pattern Anal. Mach. Intell. 15(12): 1217-1232 (1993) |