F. Heitz

发表

Multiscale minimization of global energy functions in some visual recovery problems

P. Pérez, P. Bouthemy, F. Heitz, 1994 .

Parallel visual motion analysis using multiscale Markov random fields

P. Pérez, P. Bouthemy, F. Heitz, 1991, Proceedings of the IEEE Workshop on Visual Motion.

A joint physics-based statistical deformable model for multimodal brain image analysis

G. Bueno, F. Heitz, C. Nikou, 2001, IEEE Transactions on Medical Imaging.

A Topology Preserving Non-rigid Registration Method Using a Symmetric Similarity Function-Application to 3-D Brain Images

Fabrice Heitz, Jean-Paul Armspach, Vincent Noblet, 2004, ECCV.

A Bayesian approach to object detection using probabilistic appearance-based models

P. Charbonnier, F. Heitz, Rozenn Dahyot, 2004 .

Robust visual recognition of colour images

P. Charbonnier, F. Heitz, Rozenn Dahyot, 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

Unsupervised Texture Segmentation 31 30

C. Kervrann, F. Heitz, 2007 .

Eecient Parallel Non-linear Multigrid Relaxation Algorithms for Low-level Vision Applications Eecient Parallel Non-linear Multigrid Relaxation Algorithms for Low-level Vision Applications

F. Heitz, F. Heitz, 2007 .

31 30 4 Experimental Results

C. Kervrann, F. Heitz, 1999 .

Registration of MR/MR and MR/SPECT Brain Images by Fast Stochastic Optimization of Robust Voxel Similarity Measures

Fabrice Heitz, Jean-Paul Armspach, Christophoros Nikou, 1998, NeuroImage.

Introducing shape constraints into object-based traveltime tomography

P. Charbonnier, F. Heitz, P. Côté, 2016 .

Statistical model-based estimation and tracking of non-rigid motion

Patrick Pérez, Charles Kervrann, Fabrice Heitz, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Learning structure and deformation modes of nonrigid objects in long image sequences

C. Kervrann, F. Heitz, 2007 .

An A Contrario Approach for Change Detection in 3D Multimodal Images: Application to Multiple Sclerosis in MRI

F. Rousseau, S. Faisan, F. Heitz, 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution

Fabrice Heitz, Jean-Paul Armspach, Lucien Rumbach, 2003, NeuroImage.

Spatially Constrained Online Dictionary Learning for Source Separation

Fabrice Heitz, Celine Meillier, Argheesh Bhanot, 2020, IEEE Transactions on Image Processing.

Evaluation of brain atrophy estimation algorithms using simulated ground-truth data

Swati Sharma, Fabrice Heitz, Jean-Paul Armspach, 2010, Medical Image Anal..

A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction

Fabrice Heitz, Jean-Paul Armspach, Christian Heinrich, 2008, EURASIP J. Adv. Signal Process..

A robust statistics-based global energy function for the alignment of serially acquired autoradiographic sections

Fabrice Heitz, Jean-Paul Armspach, Astrid Nehlig, 2003, Journal of Neuroscience Methods.

Generalized likelihood ratio tests for change detection in diffusion tensor images: Application to multiple sclerosis

Fabrice Heitz, Jean-Paul Armspach, Vincent Noblet, 2012, Medical Image Anal..

Generalized likelihood ratio tests for change detection in diffusion tensor images

Fabrice Heitz, Jean-Paul Armspach, Vincent Noblet, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Statistical deformable model-based segmentation of image motion

Charles Kervrann, Fabrice Heitz, C. Kervrann, 1999, IEEE Trans. Image Process..

A massively parallel approach to deformable matching of 3D medical images via stochastic differential equations

Fabrice Heitz, Guy-René Perrin, Jean-Paul Armspach, 2005, Parallel Comput..

Restriction of a Markov random field on a graph and multiresolution statistical image modeling

Patrick Pérez, Fabrice Heitz, P. Pérez, 1996, IEEE Trans. Inf. Theory.

Restriction of a Markov random field on a graph and multiresolution image analysis

Fabrice Heitz, Patrick Perez, Patrick Perez, 1994 .

Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.

Laurent Thoraval, Jean-Paul Armspach, Marie-Noëlle Metz-Lutz, 2005, Academic radiology.

Discrete Markov image modeling and inference on the quadtree

Patrick Pérez, Fabrice Heitz, Jean-Marc Laferté, 2000, IEEE Trans. Image Process..

A multiresolution EM algorithm for unsupervised image classification

Patrick Pérez, Fabrice Heitz, Jean-Marc Laferté, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Topology preserving deformable image matching using constrained hierarchical parametric models

Fabrice Heitz, Jean-Paul Armspach, Olivier Musse, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks

Vincent Agnus, Vincent Noblet, Fabrice Heitz, 2019, International Journal of Computer Assisted Radiology and Surgery.

Parallel Differential Evolution: Application to 3-D Medical Image Registration

Fabrice Heitz, Guy-René Perrin, Jean-Paul Armspach, 2005 .

Unsupervised learning-based long-term superpixel tracking

Fabrice Heitz, Gwénolé Quellec, Mathieu Lamard, 2019, Image Vis. Comput..

Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields

Patrick Bouthemy, Fabrice Heitz, P. Bouthemy, 1993, IEEE Trans. Pattern Anal. Mach. Intell..

Event detection in multisource imaging: application to fine arts painting analysis

Fabrice Heitz, Henri Maître, Charles de Couessin, 1990, IEEE Trans. Acoust. Speech Signal Process..

Application of autoregressive models to fine arts painting analysis

Henri Maitre, F. Heitz, C. de Couessin, 1987 .

Disentangling high-level factors and their features with Conditional Vector Quantized VAEs

F. Heitz, S. Valette, S. Faisan, 2023, Pattern Recognition Letters.

Joint Disentanglement of Labels and Their Features with VAE

F. Heitz, S. Valette, S. Faisan, 2022, 2022 IEEE International Conference on Image Processing (ICIP).

Affine-invariant geometric shape priors for region-based active contours

Fabrice Heitz, Pierre Charbonnier, Alban Foulonneau, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Three-dimensional segmentation of anatomical structures in MR images on large data bases.

O Musse, J P Armspach, G Bueno, 2001, Magnetic resonance imaging.

Global non-linear multigrid optimization for image analysis tasks

J.-M. Laferte, P. Perez, F. Heitz, 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

Hierarchical Markov random field models applied to image analysis: a review

Francoise J. Preteux, Fabrice Heitz, Marc Sigelle, 1995, Optics + Photonics.

Disentangled representations: towards interpretation of sex determination from hip bone

F. Heitz, P. Croisille, S. Valette, 2021, The Visual Computer.

Brain segmentation from 3D MRI using statistically learned physics-based deformable models

Jean-Paul Armspach, Fabrice Heitz, Christophoros Nikou, 1998, 1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255).

On the estimation and correction of bias in local atrophy estimations using example atrophy simulations

Swati Sharma, Fabrice Heitz, Lucien Rumbach, 2013, Comput. Medical Imaging Graph..

Motion estimation and segmentation using a global Bayesian approach

Patrick Bouthemy, Fabrice Heitz, P. Bouthemy, 1990, International Conference on Acoustics, Speech, and Signal Processing.

On the modeling, construction, and evaluation of a probabilistic atlas of brain perfusion

Fabrice Heitz, Jean-Paul Armspach, Torbjørn Vik, 2005, NeuroImage.

Robust Supervoxel Matching Combining Mid-Level Spectral and Context-Rich Features

Fabrice Heitz, Gwénolé Quellec, Mathieu Lamard, 2018, Patch-MI@MICCAI.

Long-term superpixel tracking using unsupervised learning and multi-step integration

Fabrice Heitz, Gwénolé Quellec, Mathieu Lamard, 2018, 2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP).

Hierarchical multi-scale supervoxel matching using random forests for automatic semi-dense abdominal image registration

Fabrice Heitz, Pierre-Henri Conze, Vincent Noblet, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans

Fabrice Heitz, Pierre-Henri Conze, Vincent Noblet, 2017, International Journal of Computer Assisted Radiology and Surgery.

Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models

Sylvain Faisan, Laurent Thoraval, Jean-Paul Armspach, 2005, IEEE Transactions on Medical Imaging.

Affine-Invariant Multi-reference Shape Priors for Active Contours

Fabrice Heitz, Pierre Charbonnier, Alban Foulonneau, 2006, ECCV.

Geometric shape priors for region-based active contours

Fabrice Heitz, Pierre Charbonnier, Alban Foulonneau, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

A Hierarchical Markov Modeling Approach for the Segmentation and Tracking of Deformable Shapes

Charles Kervrann, Fabrice Heitz, C. Kervrann, 1998, Graph. Model. Image Process..

Multi-Reference Shape Priors for Active Contours

Fabrice Heitz, Pierre Charbonnier, Alban Foulonneau, 2008, International Journal of Computer Vision.

Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors

Fabrice Heitz, Antoine Grigis, Jean-Paul Armspach, 2012, NeuroImage.

Change Detection in Diffusion MRI Using Multivariate Statistical Testing on Tensors

Fabrice Heitz, Antoine Grigis, Jean-Paul Armspach, 2010, MICCAI.

Hybrid atlas-based and image-based approach for segmenting 3D brain MRIs

Fabrice Heitz, Jean-Paul Armspach, Gloria Bueno, 2001, SPIE Medical Imaging.

Fast deformable matching of 3D images over multiscale nested subspaces. Application to atlas-based MRI segmentation

Jean-Paul Armspach, Fabrice Heitz, Olivier Musse, 2003, Pattern Recognit..

3D deformable image matching using multiscale minimization of global energy functions

Fabrice Heitz, Jean-Paul Armspach, Olivier Musse, 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

A Bayesian approach to object detection using probabilistic appearance-based models

Fabrice Heitz, Pierre Charbonnier, Rozenn Dahyot, 2004, Pattern Analysis and Applications.

Hidden Markov multiple event sequence models: A paradigm for the spatio-temporal analysis of fMRI data

Sylvain Faisan, Fabrice Heitz, Laurent Thoraval, 2007, Medical Image Anal..

Unsupervised Nonlinear Manifold Learning

Fabrice Heitz, Jean-Paul Armspach, Christian Heinrich, 2007, 2007 IEEE International Conference on Image Processing.

Robust Pose Estimation and Recognition Using Non-Gaussian Modeling of Appearance Subspaces

Fabrice Heitz, Pierre Charbonnier, Torbjørn Vik, 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Mean shift-based Bayesian image reconstruction into visual subspace

Fabrice Heitz, Pierre Charbonnier, Torbjørn Vik, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

Statistical Atlas-Based Detection of Abnormalities in Brain Perfusion: Comparing Models and Estimating Detection Performance

Fabrice Heitz, Jean-Paul Armspach, Torbjørn Vik, 2003, MICCAI.

A low complexity approximation of probabilistic appearance models

Fabrice Heitz, Raouf Hamdan, Laurent Thoraval, 2003, Pattern Recognit..

Anomaly Detection in Single Subject vs Group Using Manifold Learning

Sylvain Faisan, Vincent Noblet, Florian Tilquin, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Data-driven curvilinear reconstructions of 3D MR images: application to cryptogenic extratemporal epilepsy.

O Musse, F Heitz, D Grucker, 1998, Magnetic resonance imaging.

A hierarchical statistical framework for the segmentation of deformable objects in image sequences

Charles Kervrann, Fabrice Heitz, C. Kervrann, 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

Which is the most appropriate strategy for conducting multivariate voxel-based group studies on diffusion tensors?

Vincent Noblet, Julien Lamy, Alix Bouchon, 2016, NeuroImage.

Which Manifold Should be Used for Group Comparison in Diffusion Tensor Imaging?

Fabrice Heitz, Jean-Paul Armspach, Vincent Noblet, 2015, MICCAI.

Longitudinal change detection: Inference on the diffusion tensor along white matter pathways

Fabrice Heitz, Antoine Grigis, Jean-Paul Armspach, 2013, Medical Image Anal..

Longitudinal Change Detection: Inference on the Diffusion Tensor Along White-Matter Pathways

Fabrice Heitz, Antoine Grigis, Jean-Paul Armspach, 2011, MICCAI.