Jean-Philippe Thiran

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Facial expressions are probably the most visual method to convey emotions and one of the most powerful means to relate to each other. A typical automatic system for the recognition of facial expressions is based on a representation of the expression, learned from a training set of pre-selected meaningful features. The learning process relies on the labels associated by an expert or a group of experts to the training samples. The experts are asked to associate each images in the training set to one of the ex

Constrained Spherical Deconvolution (CSD) is a state-of-the-art technique for unraveling complex fiber configurations of white matter from diffusion MRI data. Despite its ability to identify multiple fiber orientations, it faces difficulties in resolving f ...

Motivation: In multiple sclerosis, slowly expanding lesions have been suggested as a hallmark of a steadily worsening disease course. However, identifying these lesions is challenging, as their growth rates are at the detection limit of today's processing algorithms or MRI data must be available over a long period of time. Goal(s): To identify and characterise slowly expanding lesions in cross-sectional data. Approach: We compared changes in quantitative T1, T2 and T2/T1-ratio inside lesions and in perilesi

In this paper, we propose an analytical low-level representation of images, obtained by a decomposition process, namely the matching pursuit (MP) algorithm, as a new way of describing objects through a general continuous description using an affine invaria ...

We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this validation study. Two of them are based on Finite Gaussian Mixture (FGM) model. The first one consists only in pure gaussian distributions (FGM-EM). The second one uses a different model for partial volume (PV) (FGM-GA). The third one is based on a Hidden Markov Random Field (HMRF) model. All methods have been tested on a Digital Brain Phantom i

Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function relationship, have l ...

This paper describes a technique for identifying the boundary of the optic disk in digital images of the retina, using an approach based on active contours (snakes). The optic disk is the region on the retina at which optic nerve axons enter and leave the eye. Changes in optic disk shape and area may indicate disease processes, particularly glaucoma, and accurate identification of the disk boundary may be used to quantify changes. For accurate boundary identification, some pre-processing of the image is nec

In order to better understand the high complexity of the brain, the detailed study of its individual components clearly seems insufficient. The backbone of complexity in the nervous system is composed of the large scale architectural characteristics of the neuronal network. Newly, by the advent of MR tractography, its investigation is accessible. We report on two important network characteristics that were already guessed from functional investigations and animal ex vivo studies, but never directly addresse

Enhanced behavioral interventions are gaining increasing interest as innovative treatment strategies for major depressive disorder (MDD). In this study protocol, we propose to examine the synergistic effects of a self-administered home-treatment, encompass ...

In this paper, we introduce a new template-based spectral nonrigid registration method in which the target is represented using multilevel partition of unity (MPU) implicit surfaces and the template is embedded in a discrete Laplace-Beltrami based spectral ...

For radiotherapy treatment planning of retinoblastoma in childhood, Computed Tomography (CT) represents the standard method for tumor volume delineation, despite some inherent limitations. CT scan is very useful in providing information on physical density ...

Diffusion MRI (dMRI) represents one of the few methods for mapping brain fiber orientations non-invasively. Unfortunately, dMRI fiber mapping is an indirect method that relies on inference from measured diffusion patterns. Comparing dMRI results with other ...

Extreme prematurity and pregnancy conditions leading to intrauterine growth restriction (IUGR) affect thousands of newborns every year and increase their risk for poor higher order cognitive and social skills at school age. However, little is known about t ...

This paper proposes an application of information theoretic approach for finding the most informative subset of eigenfeatures to be used for audio-visual speech recognition tasks. The state-of-the-art visual feature extraction methods in the area of speechreading rely on either pixel or geometric based methods or their combination. However, there is no common rule defining how these features have to be selected with respect to the chosen set of audio cues and how well they represent the classes of the utter

One of the major limitations of diffusion MRI tractography is that the fiber tracts recovered by existing algorithms are not truly quantitative. Local techniques for estimating more quantitative features of the tissue microstructure exist, but their combin ...

Medical image segmentation is an important task forcomputer aided diagnosis. Pixelwise manual annotationsof large datasets require high expertise and is time consum-ing. Conventional data augmentations have limited benefitby not fully representing the unde ...

In this paper we propose a new approach to automatic human face detection which employs anisotropic Gaussian filters as local image descriptors. We then show how the paradigm of classifier combination can be used for building a face detector that outperforms the current state of the art systems, while remaining fast enough for being used in real time systems. We report a number of results on some reference datasets and we use an unbiased method for comparing the detectors.

Earth observation is taking more and more importance in our society. Indeed, recent technologies march allows for satellite images to get ground resolution up to less than one meter. Thus, most of satellite image information obtained begins now to be widely used for multiple purposes ranging from cartography and mapping to agricultural management and security applications. Among all the satellite imaging systems, Synthetic Aperture Radar (or SAR) are very interesting for global earth surveillance and monito

Objects Deep brain stimulation (DBS) has turned out to be the surgical technique of choice for the treatment of movement disorders, e.g. Parkinson s disease (PD), the usual target being the subthalamic nucleus (STN). The targeting of such a small structure is crucial for the outcome of the surgery. Unfortunately the STN is in general not easily distinguishable in common medical images. Material and Methods Eight bilaterally implanted PD patients were considered (16 STNs). A three-dimensional MR T1-weighted

Detecting faces in images is a key step in numerous computer vision applications, such as face recognition or facial expression analysis. Automatic face detection is a difficult task because of the large face intra-class variability which is due to the imp ...

Jean-Philippe Thiran

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Facial Expressions Evaluation Survey

Spatial Prior Informed Constrained Spherical Deconvolution in Super Resolution Variation

Cross-sectional multiparametric subtyping of multiple sclerosis lesions informs on their longitudinal evolution

Matching pursuit-based shape representation and recognition using scale-space

Validation of Tissue Modelization and Classification Techniques in T1-Weighted MR Brain Images

HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification

Identification of the optic disk boundary in retinal images using active contours

Imaging the brain neuronal network with diffusion MRI: a way to understand its global architecture

Examining the synergistic effects of a cognitive control video game and a home-based, self-administered non-invasive brain stimulation on alleviating depression: the DiSCoVeR trial protocol

3D Spectral Nonrigid Registration of Facial Expression Scans

Model-based Segmentation and Image Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain

Structural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition

Mutual information eigenlips for audio-visual speech recognition

Microstructure informed tractography: pitfalls and open challenges

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

Anisotropic Gaussian Filters for Face Class Modeling

Exploiting Multi-Temporal Information for SAR Image Segmentation

Feature-segmentation-based registration for fast and accurate deep brain stimulation targeting

Face Detection with Boosted Gaussian Features