Jean-Philippe Thiran

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Multiple lines of evidence suggest that schizophrenia is associated with abnormalities in neural circuitry and impaired structural connectivity. Although largely investigated by imaging studies, very few results have been published on in-vivo image-based connectivity investigations, and those published report often contradictory findings. In this study, we propose to conduct a group study to evaluate the differences in structural connectivity between schizophrenic patients and control subjects using Diffusi

Children with congenital heart disease (CHD) who survive surgery often present impaired neurodevelopment and qualitative brain anomalies. However, the impact of CHD on total or regional brain volumes only received little attention. We address this question ...

In this paper, a fast and effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose, we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier extracts faces of any pose from the background. Then, more specific classifiers discriminate between different poses. The tree of classifiers is trained by hierarchically sub-sampling the pose space. Finally, Condensation algorithm is used for tracking the f

We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the probability density functions of both regions within the optimization process ...

Essential tremor (ET) is the most common movement disorder. Deep brain stimulation is the current gold standard for drug-resistant tremor, followed by radiofrequency lesioning. Stereotactic radiosurgery by Gamma Knife (GK) is considered as a minimally inva ...

Multi-component T2 relaxometry allows probing tissue microstructure by assessing compartment-specific T2 relaxation times and water fractions, including the myelin water fraction. Non-negative least squares (NNLS) with zero-order Tikhonov regularization is ...

Objectives Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize micro ...

Littering quantification is an important step for improving cleanliness of cities. When human interpretation is too cumbersome or in some cases impossible, an objective index of cleanliness could reduce the littering by awareness actions. In this paper, we ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

Thalamic nuclei can be distinguished by their characteristic fiber orientations, which influence the diffusion. Fiber orientations are relatively aligned within a nucleus due to the fact that the cerebrocortical striations within a nucleus all target the s ...

Quality assessment of MRI is of great importance to derive reliable diagnostic information. As automated quantitative image analysis is being increasingly used in routine, automated measures of quality are needed. Based on a single magnitude image, we prop ...

We propose a new approach for image segmentation at different scales of observation, based on a multiscale image decomposition and on the active contour segmentation model. The proposed method consists of two steps. Firstly, a representation of a given image at multiple scales is derived, by means of a smoothing method which minimizes the weighted total variation norm of the image. This method allows the longtime preservation of edges and contrast with increasing scale, facilitating the detection of underly

This paper introduces a two-steps adaptive generalized Hough transform (GHT) for the detection of non-analytic objects undergoing weak affine transformations in images. The first step of our algorithm coarsely locates the region of interest with a GHT for similitudes. The returned detection is then used by an adaptive GHT for affine transformations. The adaptive strategy makes the computation more amenable and ensures high accuracy, while keeping the size of the accumulator array small. To account for the d

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this paper, we propose a scalable algorithm f ...

Visual inspection with acetic acid (VIA) is one of the methods recommended by the World Health Organization for cervical cancer screening. VIA is simple and low-cost; it, however, presents high subjectivity. We conducted a systematic literature search in P ...

The methodological development in the mapping of the brain structural connectome from diffusion-weighted mag-netic resonance imaging (DW-MRI) has raised many hopes in the neuroscientific community. Indeed, the knowledge of the connections between different ...

Axon Diameter Distributions (ADDs) change during brain development and are altered in several brain pathologies. Mapping ADDs non-invasively using dMRI could provide a useful biomarker, but existing methods are either parametric, orientation dependent, sur ...

The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and mos ...

3D ultrasound (US) acquisition acquires volumetric images, thus alleviating a classical US imaging bottleneck that requires a highly-trained sonographer to operate the US probe. However, this opportunity has not been explored in practice, since 3D US machi ...

Combining several classifiers has proved to be an effective machine learning technique. Two concepts clearly influence the performances of an ensemble of classifiers: the diversity between classifiers and the individual accuracies of the classifiers. In th ...

Jean-Philippe Thiran

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Schizophrenia connectivity investigation by DTI Tractography

Regional cortical volumes and congenital heart disease: a MRI study in 22q11.2 deletion syndrome

Fast multi-view face tracking with pose estimation

Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions

The Brain Connectome after Gamma Knife Radiosurgery of the Ventro-Intermediate Nucleus for Tremor: Marseille-Lausanne Radiobiology Study Protocol

Comparison of non-parametric T2 relaxometry methods for myelin water quantification

Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis

A Computer Vision System to Localize and Classify Wastes on the Streets

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Thalamic nuclei clustering on High Angular Resolution Diffusion Images

Automatic quality assessment in structural brain magnetic resonance imaging

Multiscale Image Segmentation Using Active Contours

Adaptive Hough transform for the detection of natural shapes under weak affine transformations

A scalable algorithm for radio-interferometric imaging

Artificial Intelligence-Based Cervical Cancer Screening on Images Taken during Visual Inspection with Acetic Acid: A Systematic Review

The diffusion-simulated connectivity (DiSCo) dataset

Orientation invariant and non-parametric Axon Diameter Distribution mapping using PGSE and regularized discrete linear modeling

Understanding Diffusion MR Imaging Techniques: From Scalar Diffusion-weighted Imaging to Diffusion Tensor Imaging and Beyond

Single-FPGA complete 3D and 2D medical ultrasound imager

Information theoretic combination of pattern classifiers