Publications de Xavier Bresson

Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems

Jean-Philippe Thiran, Pierre Vandergheynst, Xavier Bresson, Patric Hagmann, Alessandra Griffa, Alessandro Daducci, Kirell Maël Benzi, Benjamin Ricaud

The study of brain dynamics enables us to characterize the time-varying functional connectivity among distinct neural groups. However, current methods suffer from the absence of structural connectivity information. We propose to integrate infra-slow neural ...

Elsevier2017

Consistency of Cheeger and Ratio Graph Cuts

Xavier Bresson

This paper establishes the consistency of a family of graph-cut-based algorithms for clustering of data clouds. We consider point clouds obtained as samples of a ground-truth measure. We investigate approaches to clustering based on minimizing objective fu ...

Microtome Publishing2016

Source Localization on Graphs via l1 Recovery and Spectral Graph Theory

Pierre Vandergheynst, Xavier Bresson, Rodrigo Cerqueira Gonzalez Pena

We cast the problem of source localization on graphs as the simultaneous problem of sparse recovery and diffusion ker- nel learning. An l1 regularization term enforces the sparsity constraint while we recover the sources of diffusion from a single snapshot ...

Ieee2016

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Pierre Vandergheynst, Xavier Bresson, Michaël Defferrard

In this work, we are interested in generalizing convolutional neural networks (CNNs) from low-dimensional regular grids, where image, video and speech are represented, to high-dimensional irregular domains, such as social networks, brain connectomes or wor ...

2016

Song Recommendation with Non-Negative Matrix Factorization and Graph Total Variation

Pierre Vandergheynst, Xavier Bresson, Kirell Maël Benzi, Vasilis Kalofolias

This work formulates a novel song recommender system as a matrix completion problem that benefits from collaborative filtering through Non-negative Matrix Factorization (NMF) and content-based filtering via total variation (TV) on graphs. The graphs encode ...

Ieee2016

Robust Principal Component Analysis on Graphs

Pierre Vandergheynst, Xavier Bresson, Vasilis Kalofolias, Nauman Shahid, Michael Bronstein

Principal Component Analysis (PCA) is the most widely used tool for linear dimensionality reduction and clustering. Still it is highly sensitive to outliers and does not scale well with respect to the number of data samples. Robust PCA solves the first iss ...

2015

Mapping resting-state dynamics on spatio-temporal graphs: a combined functional and diffusion MRI approach

Jean-Philippe Thiran, Pierre Vandergheynst, Xavier Bresson, Patric Hagmann, Alessandra Griffa, Kirell Maël Benzi, Benjamin Ricaud

2015

Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

Meritxell Bach Cuadra, Xavier Bresson, Anca-Ramona Ciurte

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to ...

Institute of Electrical and Electronics Engineers2014

Harmonic Active Contours

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso, Virginia Estellers Casas

We propose a segmentation method based on the geometric representation of images as two-dimensional manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set ...

Institute of Electrical and Electronics Engineers2014

Semi-Supervised Segmentation of Ultrasound Images Based on Patch Representation and Continuous Min Cut

Jean-Philippe Thiran, Meritxell Bach Cuadra, Olivier Cuisenaire, Xavier Bresson, Nawal Houhou, Anca-Ramona Ciurte

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the ...

Public Library Science2014

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the da ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Matrix Completion on Graphs

Pierre Vandergheynst, Xavier Bresson, Vasilis Kalofolias, Michael Bronstein

The problem of finding the missing values of a matrix given a few of its entries, called matrix completion, has gathered a lot of attention in the recent years. Al- though the problem under the standard low rank assumption is NP-hard, Cande`s and Recht sho ...

2014

Enhanced Compressed Sensing Recovery with Level Set Normals

Jean-Philippe Thiran, Xavier Bresson, Virginia Estellers Casas

We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the i ...

2013

An Efficient Algorithm for Level Set Method Preserving Distance Function

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso, Virginia Estellers Casas

The level set method is a popular technique for tracking moving interfaces in several disciplines including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issue ...

Institute of Electrical and Electronics Engineers2012

Geodesic Active Fields - A Geometric Framework for Image Registration

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inve ...

Institute of Electrical and Electronics Engineers2011

Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation using the Active Contour Framework

Valérie Duay, Jean-Philippe Thiran, Meritxell Bach Cuadra, Xavier Bresson, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and ...

Elsevier2011

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Jean-Philippe Thiran, Alessia Pica, Meritxell Bach Cuadra, Xavier Bresson, Nawal Houhou, Anca-Ramona Ciurte

Segmenting ultrasound images is a challenging problem where standard unsupervised segmentation methods such as the well-known Chan-Vese method fail. We propose in this paper an efficient segmentation method for this class of images. Our proposed algorithm ...

2011

Harmonic Active Contours for multichannel image segmentation

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso, Virginia Estellers Casas

We propose a segmentation method based on the geometric representation of images as surfaces embedded in a higher dimensional space, handling naturally multichannel images. The segmentation is based on an active contour embedded in the image manifold, alon ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Geodesic Active Fields - A Geometric Framework for Image Registration

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inve ...

Amer Inst Physics, 2 Huntington Quadrangle, Ste 1No1 D, Melville, Ny 11747-4501 Usa2010

Semi-Supervised Segmentation based on Non-local Continuous Min-Cut

Jean-Philippe Thiran, Xavier Bresson, Nawal Houhou

We propose a semi-supervised image segmentation method that relies on a non-local continuous version of the min-cut algorithm and labels or seeds provided by a user. The segmentation process is performed via energy minimization. The proposed energy is comp ...

Springer2009