Jean-Philippe Thiran

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Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this is ...

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

Probabilistic parameter estimation in model fitting runs the gamut from maximum likelihood or maximum a posteriori point estimates from optimization to Markov Chain Monte Carlo (MCMC) sampling. The latter, while more computationally intensive, generally pr ...

Diffusion-weighted magnetic resonance imaging (DW-MRI) tractography is a non-invasive tool to probe neural connections and the structure of the white matter. It has been applied successfully in studies of neurological disorders and normal connectivity. Rec ...

Very preterm birth (VPT;

In vivo fetal magnetic resonance imaging provides a unique approach for the study of early human brain development [1]. In utero cerebral morphometry could potentially be used as a marker of the cerebral maturation and help to distinguish between normal and abnormal development in ambiguous situations. However, this quantitative approach is a major challenge because of the movement of the fetus inside the amniotic cavity, the poor spatial resolution provided by very fast MRI sequences and the partial volume

Functional imaging studies have shown that information relevant to sound recognition and sound localization are processed in anatomically distinct cortical networks. We have investigated the functional organization of these specialized networks by evaluating acute effects of circumscribed hemispheric lesions. Thirty patients with a primary unilateral hemispheric lesion, 15 with right-hemispheric damage (RHD) and 15 with left-hemispheric damage (LHD), were evaluated for their capacity to recognise environmen

Whether different brain networks are involved in generating unimanual responses to a simple visual stimulus presented in the ipsilateral versus contralateral hemifield remains a controversial issue. Visuo-motor routing was investigated with event-related f ...

Developing computational pathology models is essential for reducing manual tissue typing from whole slide images, transferring knowledge from the source domain to an unlabeled, shifted target domain, and identifying unseen categories. We propose a practica ...

Despite recent improvements, complete motor recovery occurs in < 15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the preci ...

Background and objectives: In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform ...

In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally co ...

Introduction. Development of the fetal brain surface with concomitant gyrification is one of the major maturational processes of the human brain. First delineated by postmortem studies or by ultrasound, MRI has recently become a powerful tool for studying in vivo the structural correlates of brain maturation. However, the quantitative measurement of fetal brain development is a major challenge because of the movement of the fetus inside the amniotic cavity, the poor spatial resolution, the partial volume ef

In this pilot study, we present a new engineering approach to reconstruct a patient-specific model of the fetal head near term. Indeed, 3D visualization of the fetus prominent skull could help the obstetricians in decision-making to overcome dystocia, a de ...

Tractography enables identifying and evaluating the healthy and diseased brain's white matter pathways from diffusion-weighted magnetic resonance imaging data. As previous evaluation studies have reported significant false-positive estimation biases, recen ...

The accurate estimation of fiber orientation distribution functions (fODFs) in diffusion magnetic resonance imaging (MRI) is crucial for understanding early brain development and its potential disruptions. Although supervised deep learning (DL) models have shown promise in fODF estimation from neonatal diffusion MRI (dMRI) data, the out‐of‐domain (OOD) performance of these models remains largely unexplored, especially under diverse domain shift scenarios. This study evaluated the robustness of three state‐o

Motivation. The study of human brain development in its early stage is today possible thanks to in vivo fetal magnetic resonance imaging (MRI) techniques. A quantitative analysis of fetal cortical surface represents a new approach which can be used as a marker of the cerebral maturation (as gyration) and also for studying central nervous system pathologies [1]. However, this quantitative approach is a major challenge for several reasons. First, movement of the fetus inside the amniotic cavity requires very

With the emergence of ultra-portable ultrasound systems, the need to reduce cost and complexity of ultrasound systems has intensified. Sparse arrays, employing fewer transducer elements to acquire images, offer a viable solution by effectively minimizing d ...

A recent internet based survey of over 35'000 samples has shown that when different human observers are asked to assign labels to static human facial expressions, different individuals categorize differently the same image. This fact results in a lack of a ...

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

Jean-Philippe Thiran

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Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

White adipose tissue distribution and amount are associated with increased white matter connectivity

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

On the cortical connectivity in the macaque brain: A comparison of diffusion tractography and histological tracing data

Cortical alterations after very preterm birth and the association with socio-emotional abilities from childhood to early adolescence

Quantitative morphometry analysis of the fetal brain using clinical MR imaging

Sound recognition and localization in man: specialized cortical networks and effects of acute circumscribed lesions

Visuo-motor pathways in humans revealed by event-related fMRI

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Toward individualized medicine in stroke-The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis

Predicting Human Resting-State Functional Connectivity from structural Connectivity

A post-processing pipeline to reconstruct the developing fetal brain using low-resolution MRI

Reconstruction of Fetal Head Surface from Few 2D Ultrasound Images Tracked in 3D Space

Evaluating reproducibility and subject-specificity of microstructure-informed connectivity

Deep Learning for fODF Estimation in Infant Brains: Model Comparison, Ground-Truth Impact, and Domain Shift Mitigation

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Sequential CNN-based Enhancement of Ultrafast Ultrasound Imaging for Sparse Arrays

Modelling human perception of static facial expressions

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation