Fabrice Heitz

Disentangled representations: towards interpretation of sex determination from hip bone

By highlighting the regions of the input image that contribute the most to the decision, saliency maps have become a popular method to make neural networks interpretable. In medical imaging, they...

Unsupervised learning-based long-term superpixel tracking

Finding correspondences between structural entities decomposing images is of high interest for computer vision applications. In particular, we analyze how to accurately track superpixels - visual...

Hierarchical Statistical Models for the Fusion of Multiresolution Image Data

General linear models for group studies in diffusion tensor imaging

Lubrav: A New Framework For The Segmentation Of The Lung's Tubular Structures

A new high order tensor decomposition: Application to reorientation

Random forests on hierarchical multi-scale supervoxels for liver tumor segmentation in dynamic contrast-enhanced CT scans

Generalized Likelihood Ratio Tests for Change Detection in Diffusion Tensor Images

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

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

Single- and multimodal subvoxel registration of dissimilar medical images using robust similarity measures

Unsupervised spatio-temporal detection of brain functional activation based on hidden Markov multiple event sequence models

3D watershed-based segmentation of internal structures within MR brain images

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

Probabilistic multiobject deformable model for MR/SPECT brain image registration and segmentation

3D deformable image matching: a hierarchical approach over nested subspaces

3D Deformable Image Matching Using Multiscale Minimization of Global Energy Functions

Efficient parallel multigrid relaxation algorithms for Markov random field-based low-level vision applications