Jean-Philippe Thiran

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In this paper we present a novel framework called geodesic active fields for general image registration on Riemannian manifolds. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. In this paper, we define a new geometric approach to image registration. More specifically, we propose to embed the deformation field in a higher dimensional manifold. Then

In this study we investigated the effect of medial temporal lobe epilepsy (MTLE) on the global characteristics of brain connectivity estimated by topological measures. We used DSI (Diffusion Spectrum Imaging) to construct a connectivity matrix where the no ...

Ultrasound imaging is a reference medical diagnostic technique, thanks to its blend of versatility, effectiveness, and moderate cost. The core computation of all ultrasound imaging methods is based on simple formulae, except for those required to calculate ...

Development of technologies in the field of neuroimaging brought an increase interest in the quantification of cortical folding (gyrification), notably for neurogenetic and psychiatric disorders that may result from an early abnormal cortical development. For example, gyrification has been reported altered in schizophrenia (Kulynych, 1997; Harris, 2004), autism (Hardan, 2004), and Williams syndrome (Schmitt, 2002). Algorithms traditionally used to quantify gyrification measure the cortical perimeter on two-

Very often, the only reliable information available to perform change detection is the description of some unchanged regions. Since sometimes these regions do not contain all the relevant information to identify their counterpart (the changes), we consider ...

OBJECTIVE Essential tremor (ET) is the most common movement disorder. Drug-resistant ET can benefit from standard stereotactic deep brain stimulation or radiofrequency thalamotomy or, alternatively, minimally invasive techniques, including stereotactic rad ...

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion MRI data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the ne ...

Diffusion magnetic resonance imaging is a noninvasive imaging modality that has been extensively used in the literature to study the neuronal architecture of the brain in a wide range of neurological conditions using tractography. However, recent studies h ...

Reducing radio frequency data volume prior to beamforming is crucial for enabling efficient 3D imaging and ultraportable devices. In previous work, we introduced a convolutional neural network (CNN)-based inpainting method designed to estimate missing radio frequency (RF) data from single plane waves (PWs) acquired with sparse arrays in reception. Motivated by the superior image quality achievable through compounding multiple PWs, we extend the inpainting method for multi-PW acquisitions. To ensure fair com

Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in the design of the biomimicking geometrical configurations ...

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2, several methods exist to q ...

Automatic emotion recognition systems based on supervised machine learning require reliable annotation of affective behaviours to build useful models. Whereas the dimensional approach is getting more and more popular for rating: affective behaviours in continuous time domains, e.g., arousal and valence, methodologies to take into account reaction lags of the human raters are still rare. We therefore investigate the relevance of using machine learning algorithms able to integrate contextual information in th

Purpose A method for simultaneous mapping of static (B 0 ) and transmit (B 1 + ) field inhomogeneities at ultra‐high field (UHF) was developed and validated. The utility of accelerating the proposed sequence using deep learning (DL) and joint low‐rank tensor completion (TxLR) reconstruction methods was evaluated to enable rapid online implementation. Methods A 3D sequence, Combined caLculation of UHF Biases (CLUB)‐Sandwich, was developed by incorporating a multi‐echo readout into the unsaturated segment of

High-quality 3D ultrasound (US) imaging requires dense matrix-array probes with thousands of elements and necessitates an unrealistic number of coaxial cables to connect such probes to back-end systems. To address this issue, many techniques have been deve ...

Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniques (explainers) based on pixel-wise processing disregard biological entities ...

Volumetric ultrasound (US) is a very promising development of medical US imaging. An under-exploited advantage of volumetric US is the mitigation of the strict probe positioning constrains necessary to acquire 2D scans, potentially allowing the decoupling ...

lectrical deep brain stimulation (DBS) is an efficient method to treat movement disorders. Many models of DBS, based mostly on finite elements, have recently been proposed to better understand the interaction between the electrical stimulation and the brain tissues. In monopolar DBS, clinically widely used, the implanted pulse generator (IPG) is used as reference electrode (RE). In this paper, the influence of the RE model of monopolar DBS is investigated. For that purpose, a finite element model of the ful

Stereo vision is a usual method to obtain depth information from images. The problems encountered when applying the majority of well established algorithms to provide this information are due to the high computational load required. This occurs in both the block matching and graphical cues (such as edges) matching. In this article we address this issue by performing an image analysis which considers each pixel only once, thus enhancing the efficiency of the image processing. Additionally, when matching is c

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty ...

In this paper, we present an integrated system for real-time dose distribution calculation and treatment planning optimisation for brachytherapy of prostate cancer, with a special emphasis on the visual integration of the dosimetry and target images obtain ...

Jean-Philippe Thiran

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Geodesic Active Fields - A Geometric Framework for Image Registration

Altered structural connectivity in patients with medial temporal lobe epilepsy: A Diffusion Spectrum Imaging and Graph Analysis study

Efficient Sample Delay Calculation for 2-D and 3-D Ultrasound Imaging

A New Method For Measuring Cortical Folding In A 3D Space From MR Images

Semi-Supervised Novelty Detection using SVM entire solution path

Pretherapeutic resting-state fMRI profiles are associated with MR signature volumes after stereotactic radiosurgical thalamotomy for essential tremor

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography

A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information

Multi-Plane Wave Signal Inpainting with CNNs: A Framework for Reducing RF Data Volume in Ultrafast Ultrasound

Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Prediction of Asynchronous Dimensional Emotion Ratings from Audiovisual and Physiological Data

Combined caLculation of Ultra‐high field Biases (CLUB ) With Sandwich: Fast, Simultaneous Estimation of 3D B 0 and Multi‐Channel B 1 + Maps at 7 T

Compressive Multiplexing of Ultrasound Signals

Quantifying Explainers of Graph Neural Networks in Computational Pathology

Inexpensive 1024-Channel 3D Telesonography System on FPGA

Influence of the implanted pulse generator as reference electrode in finite element model of monopolar deep brain stimulation

Stereo Vision Matching using Characteristics Vectors

MBIS: Multivariate Bayesian Image Segmentation tool

Real-Time Treatment Planning Optimisation for Brachytherapy