Jean-Philippe Thiran

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Many works on speech processing have dealt with auto-regressive (AR) models for spectral envelope and formant frequency estimation, mostly focusing on the estimation of the AR parameters. However, it is also interesting to be able to directly estimate the ...

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

Currently, one of the gold-standard methods to obtain brain myelin water fraction (MWF) maps is the multi-echo spin-echo sequence. To overcome some of its limitations (e.g. long acquisition times), a data-driven approach for deriving MWF maps is proposed here. A general linear model (GLM) and a conditional generative adversarial network (cGAN) were trained to learn the reference MWF from T1 and T2 maps acquired in a healthy cohort. While GLM-derived maps exhibited MWF overestimation, especially in WM tissue

Although high angular resolution diffusion MRI techniques are able to solve multiple intra-voxel fiber orientations, the usual streamline Diffusion Spectrum Imaging (DSI) tractography algorithms present some limitations in their ability to map complex fibe ...

In this paper we use the theory of geometric curve and surface evolution to diffuse an object preserving their important features. We do that using a curvature flow method with a novel influence function. The proposed influence function takes profit from the characteristics of the level set representation to perform a directional diffusion improving other influence functions results that evolve in such a way that though they diffuse noise, important features are also lost after some iterations. We show that

The problem of improving image quality in ultrafast ultrasound (US) imaging by means of regularized iterative algorithms has raised a vast interest in the US community. These approaches usually rely on standard image processing priors, such as wavelet spar ...

Several nonrigid registration algorithms have been proposed for inter-subject alignment, used to construct statistical atlases and to identify group differences. Assessment of the accuracy of nonrigid registration algorithms is an essential and complex issue due to its intricate framework and its application-dependent behavior. We demonstrate that the diffusion MRI provides an independent means of assessing the quality of alignment achieved on the structural MRI. Diffusion tensor MRI (DT MRI) enables the co

Volumetric analysis of bundles derived from tractography is a popular statistical measure used in neurological disorder studies. Recent research performed by Gauvin shows that different bundles saturate with different tractography parameters, however, to a ...

We propose a method for brain atlas deformation in presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed, combining a method derived from optical flow principles and a model of lesion gr

In this paper, we propose an evolution equation for the active contours in scale spaces. This evolution equation is based on the Polyakov functional that has been first introduced in physics and has been then used in image processing in

Many clinical MRI protocols use the fluid attenuated inversion recovery (FLAIR) contrast to better delineate tissue abnormalities such as white matter lesions. Most FLAIR protocols acquire data in a 2D fashion. FLAIR images are often degraded by patient motion, especially when scanning uncooperative patients. Typical motion patterns induce inter-slice misalignment, ghosting and blurring artifacts which can obscure the pathology or mislead automated image analysis algorithms. In this work, we propose the use

Tractography has proven particularly effective for studying noninvasively the neuronal architecture of the brain but recent studies have showed that the high incidence of false positives can significantly bias any connectivity analysis. We present a novel ...

In this paper, we propose two approaches to define an evolution equation for the active contours in scale spaces. The evolution equation is based on the Polyakov functional that has been first introduced in physics and has been then used in image processing in

Zero-shot classification capabilities naturally arise in models trained within a vision-language contrastive framework. Despite their classification prowess, these models struggle in dense tasks like zero-shot open-vocabulary segmentation. This deficiency ...

Diffusion MRI is a well established imaging modality providing a powerful way to non-invasively probe the structure of the white matter. Despite the potential of the technique, the intrinsic long scan times of these sequences have hampered their use in cli ...

A quantitative measure of relevance is proposed for the task of constructing visual feature sets which are at the same time relevant and compact. A feature's relevance is given by the amount of information that it contains about the problem, while compactn ...

Jean-Philippe Thiran

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Sparse non-negative decomposition of speech power spectra for formant tracking

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Deriving Brain Myelin Water Fraction Maps from Relaxometry: a Data-Driven Approach

Editorial: Computational Pathology

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (5/6)

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (3/6)

Fast-Marching Tractography for Connection Matrix (Fast-TraC)

Unsupervised Selective Anisotropic Feature Diffusion for Cortical Surface Registration

Deep Convolutional Neural Network for Ultrasound Image Enhancement

Evaluation of brain image nonrigid registration algorithms based on Log-Euclidean MR-DTI consistency measures

When does a volume of a bundle achieve saturation? A microstructure informed tractography study

Atlas-Based Segmentation of Pathological Brain MR Images

Multiscale Active Contours

Automatic quality assessment for multi-slice 2D FLAIR MR imaging

Reducing false positives in tractography with microstructural and anatomical priors

Multiscale Active Contours

A Simple Framework for Open-Vocabulary Zero-Shot Segmentation

CLaiMS-Net: cortical lesions assessment in multiple sclerosis patients via a convolutional neural network and a single 3T MRI acquisition

l0-deconvolution for compressive diffusion MRI

Selecting relevant visual features for speechreading