Jean-Philippe Thiran

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This paper describes the development of a novel medical x-ray imaging system adapted to the needs and constraints of low- and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible ligh ...

In this paper we propose the use of Discrete Choice Analysis (DCA) for static facial expression classification. Facial expressions are described with expression descriptive units (EDU), consisting in a set of high level features derived from an active appearance model (AAM). The discrete choice model (DCM) is built considering the 6 universal facial expressions plus the neutral one as the set of the available alternatives. Each alternative is described by an utility function, defined as the sum of a linear

Driving requires the constant coordination of many body systems and full attention of the person. Cognitive distraction (subsidiary mental load) of the driver is an important factor that decreases attention and responsiveness, which may result in human err ...

Magnetic resonance imaging (MRI) probes signals through Fourier measurements. Accelerating the acquisition process is of major interest for various MRI applications. The recent theory of compressed sensing shows that sparse or compressible signals may be r ...

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 ...

Over the last ten years, Diffusion-weighted Imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little ...

Sparse arrays offer a promising solution for reducing the data volume required to reconstruct ultrasound images, making them well-suited for portable and wireless devices. However, the quality of images beamformed from a limited number of transducer elements is significantly degraded. This study proposes a deep learning-based inpainting technique to estimate complete radio frequency (RF) signals (before beamforming) from downsampled RF signals obtained using a subset of transducer elements. This approach al

We propose a deep study on tissue modelization and classification techniques on T1-weighted MR images. Six approaches have been taken into account to perform this validation study. We consider first the Finite Gaussian Mixture model (A-FGMM) and a Bayes classification. Second method is the same as A-FGMM but introducing a Hidden Markov Random Field (HMRF) model to encode spatial information and classification is then performed by Maximum a Posteriori (MAP). Third, we study a method that models mixture tissu

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

This study introduces a Machine Learning (ML) approach for estimating the T2 spectrum and myelin water fraction (MWF) using multi-echo T2 (MET2) data from preclinical 7T Magnetic Resonance Imaging (MRI) scanners. ML methods have shown promise in MWF estima ...

Although alterations in bone mineral density (BMD) at the proximal tibia have been suggested to play a role in various musculoskeletal conditions, their pathophysiological implications and their value as markers for diagnosis remain unclear. Improving our ...

Eye gaze movements are considered as a salient modality for human computer interaction applications. Recently, cross-ratio (CR) based eye tracking methods have attracted increasing interest because they provide remote gaze estimation using a single uncalib ...

In recent years, there has been notable progress in the development of inverse problems for image reconstruction in pulse-echo ultrasound. Inverse problems are designed to circumvent the restrictions of delay-And-sum, such as limited image resolution and d ...

Diffusion-weighted MRI is our most promising method for estimating microscopic tissue morphology in vivo. The signal acquisition is based on scanner-generated external magnetic gradients. However, it will also be affected by susceptibility-induced internal ...

Despite that cognitive impairment is a known early feature present in multiple sclerosis (MS) patients, the biological substrate of cognitive deficits in MS remains elusive. In this study, we assessed whether T1 relaxometry, as obtained in clinically acceptable scan times by the recent Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) sequence, may help identifying the structural correlate of cognitive deficits in relapsing-remitting MS patients (RRMS). Twenty-nine healthy controls (HC) a

Diffusion MRI (DW-MRI) allows for the detailed exploration of the brain white matter microstructure, with applications in both research and the clinic. However, state-of-the-art methods for microstructure estimation suffer from known limitations, such as t ...

Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by volumetric and functional MRI studies. Diffusion Magnetic Resonance ...

Drones have become steadily affordable, which raises privacy and security concerns as well as interest in drone detection systems. On the other hand, drone detection is a challenging task due to small dimensions of drones, difficulty of long-distance detec ...

Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the vent ...

Schizophrenia pathophysiology implies both abnormal redox control and dysconnectivity of the prefrontal cortex, partly related to oligodendrocyte and myelin impairments. As oligodendrocytes are highly vulnerable to altered redox state, we investigated the ...

Jean-Philippe Thiran

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X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries

Discrete Choice Models for Static Facial Expression Recognition

Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving

Spread spectrum for compressed sensing techniques in magnetic resonance imaging

Harmonic Active Contours for multichannel image segmentation

High b-value diffusion-weighted imaging: a sensitive method to reveal white matter differences in schizophrenia

Deep Learning-Based Inpainting for Sparse Arrays in Ultrafast Ultrasound Imaging

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

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

In-Silico Trained AI for Enhanced T2Spectrum Imaging and Myelin Water Fraction Mapping in Preclinical 7T MRI

A Registration Method for Three-Dimensional Analysis of Bone Mineral Density in the Proximal Tibia

Towards Convenient Calibration for Cross-Ratio based Gaze Estimation

An Inverse-Problem Approach to the Estimation of Despeckled and Deconvolved Images from Radio-Frequency Signals in Pulse-Echo Ultrasound

Susceptibility-induced internal gradients reveal axon morphology and cause anisotropic effects in the diffusion-weighted MRI signal

MP2RAGE provides new clinically-compatible correlates of mild cognitive deficits in relapsing-remitting multiple sclerosis

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Structural Graph Analysis of Left and Right Temporal Lobe Epilepsy using Diffusion Spectrum Imaging

Real-time high-resolution omnidirectional imaging platform for drone detection and tracking

Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study

Glutathione deficit impairs myelin maturation: relevance for white matter integrity in schizophrenia patients