Jean-Philippe Thiran

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We propose a method for brain atlas deformation in presence of large space-occupying tumors or lesions, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its central point. Atlas-based methods have been of limited use for segmenting brains that have been drastically altered by the presence of large space-occupying lesions. Our approach involves four steps. First, an affine registration brings the atlas and the patient into global correspondence. Secondly, a local r

State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framewor ...

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI da ...

This paper presents the TENECI (Collaborative tele- neurology) project which allows practitioners to use telecommunication technologies to provide medical information and services for neurological diseases. Specificities of remote neurology are described a ...

Higher risk for long-term cognitive and behavioral impairments is one of the hallmarks of extreme prematurity (EP) and pregnancy-associated fetal adverse conditions such as intrauterine growth restriction (IUGR). While neurodevelopmental delay and abnormal ...

Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Clustering mechanism (CrOC) to discove ...

A new approach for estimating inner axon radii from intra-axonal T2 relaxation times was recently proposed. However, further validations are required before this technique can be used widely. The main aim of this study is to validate this T2-based pore size estimation technique in phantoms comprising co-electrospun hollow axon-mimicking fibres designed to have non-circular cross-sections and different radii distributions. For this purpose, a diffusion-relaxation MRI dataset was acquired with a 7T preclinica

In this article, we study the adaptation of visual and audio-visual speech recognition systems to non-ideal visual conditions. We focus on overcoming the effects of a changing pose of the speaker, a problem encountered in natural situations where the speak ...

Motivation: The performance of dynamic pTx pulses might be affected by patient motion, especially in the case of long scanning sessions. Goal(s): To examine the actual impact of motion on the flip angle map of a pTx pulse optimized with a fast online customization (FOCUS) strategy. Approach: B0 and multi-channel B1+ maps were acquired at multiple head positions, and the application of the pulse optimized on the first position was simulated on the subsequent positions. Results: For various ranges of motion m

Identification of neuroimaging biomarkers following extreme prematurity (EP) and intrauterine growth restriction (IUGR) is crucial for understanding their cognitive and behavioral impairments at school age

In this paper, we have explored the effect of pose normalization for cross-pose facial expression recognition. We have first presented an expression preserving face frontalization method. After face frontalization step, for facial expression representation ...

Motivation: Standard intensity-based voxel-wise losses, generally used in image-to-image translation techniques, are typically biased towards the estimation of the low frequency content in image spectra. For the generation of synthetic CT (sCT) contrast, this results in limited image sharpness, and consequently a limited clinical utility. Goal(s): To improve sharpness in synthetic contrasts. Approach: We trained a model using a combination of intensity- and frequency-based losses for the generation of sCT i

Background: Cervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to ...

The methods of active contours (snakes) and level sets were applied to images of the retina in order to locate the outer boundary of the optic disk. A gradient-vector-flow based active contour was used as it performed well over a large range of initial conditions. Images were pre-processed to lessen the influence of blood vessels on boundary detection. Both active contours and level set methods accurately located the correct boundary; level set methods were computationally more intensive.

Most self-supervised methods for representation learning leverage a cross-view consistency objective i.e. they maximize the representation similarity of a given image's augmented views. Recent work NNCLR goes beyond the cross- view paradigm and uses positi ...

Class-specific classifiers for audio, visual and audio-visual speech recognition systems are developed and compared with traditional classifiers. We use state- of-the-art feature extraction methods and show the benefits of a class-specific classifier on ea ...

We propose a method for brain atlas deformation in presence of large space-occupying tumors or lesions, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. 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. The last step is the deformation of the seeded atlas, combining a method

Jean-Philippe Thiran

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Atlas-based Segmentation using a Model of Lesion Growth

Reducing acquisition time for axon diameter mapping using global optimization in the spatial-angular-microstructure space

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Collaborative TeleNeurology for Remote Diagnosis

Brain network characterization of high-risk preterm-born school-age children

CrOC: Cross-View Online Clustering for Dense Visual Representation Learning

Obstructive sleep apnea syndrome: effect of respiratory events and arousal on pulse wave amplitude measured by photoplethysmography in NREM sleep

Using diffusion-relaxation MRI to estimate the inner radius of co-electrospun axon-mimicking fibres

Multi-pose lipreading and audio-visual speech recognition

Evaluation of the effects of motion on dynamic pTx pulse optimization at 7T

Information Theoretic Combination of Classifiers with Application to AdaBoost

Brain Connections Associated With Socio-Cognitive Skills in Preterm and Low Birth Weight School Age Children

Face Frontalization for Cross-Pose Facial Expression Recognition

Synthetic CT generation using focal frequency loss improves image sharpness

Patient specific evaluation of the volume of tissue influenced by subthalamic nucleus (STN) deep brain stimulation (DBS) for Parkinson's Disease (PD)

Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives

Extraction of the optic disk boundary in digital fundus images

Adaptive Similarity Bootstrapping for Self-Distillation based Representation Learning

Class-specific classifiers in audio-visual speech recognition

Atlas-based Segmentation of Pathological MR Brain Images using a Model of Lesion Growth