Jean-Philippe Thiran

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Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities ...

Introduction: Medial Temporal Lobe Epilepsy (mTLE) with hippocampal sclerosis is the most frequent cause of drug-resistant focal epilepsy in adults. These patients suffer from widespread subtle white matter abnormalities and abnormal functional connectivit ...

Multi-echo T-2 magnetic resonance images contain information about the distribution of T-2 relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-neg ...

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

Pulmonary hypertension is a hemodynamic disorder defined by an abnormal elevation of pulmonary artery pressure (PAP). Current options for measuring PAP are limited in clinical practice. The aim of this study was to evaluate if electrical impedance tomograp ...

Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models are based on the assumption of negli ...

The axonal composition of cortical projections originating in premotor, supplementary motor (SMA), primary motor (a4), somatosensory and parietal areas and descending towards the brain stem and spinal cord was characterized in the monkey with histological ...

Progress in digital pathology is hindered by high-resolution images and the prohibitive cost of exhaustive localized annotations. The commonly used paradigm to categorize pathology images is patch-based processing, which often incorporates multiple instanc ...

Schizophrenia is a complex psychiatric disorder characterized by disabling symptoms and cognitive deficit. Recent neuroimaging findings suggest that large parts of the brain are affected by the disease, and that the capacity of functional integration betwe ...

Mapping the local microstructure properties of the tissue in the brain is crucial to understand any pathological condition from a biological perspective. In recent years, microstructure-imaging techniques aimed at extracting such precious information by us ...

Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context. Dimensionality reduction can alleviate computational load needed to process these data, in terms of ...

Purpose: Studies at 3T have shown that T-1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T-1 values at 7T is introduce ...

We propose here some basic approaches to direct processing of the

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-images as we take into consideration the geometry of each one. Obviously, the geometry of each of these images is a consequence of the geometry of the sensor's mirror used. This technical report is organized as follows: In the first section we develop the Laplacian operator on non-Euclidean manifolds. First we start by derivation of Laplacian operator on Riemannian manifolds and than we derive it explicitly for each of the non-Euclide

In this paper, we propose a variational model to segment an object belonging to a given scale space using the active contour method, a geometric shape prior and the Mumford-Shah functional. We define an energy functional composed by three complementary terms. The first one detects object boundaries from image gradients. The second term constrains the active contour to get a shape compatible with a statistical shape model of the shape of interest. And the third part drives globally the shape prior and the ac

Imaging the connectome in vivo has become feasible through the integration of several rapidly developing fields of science and engineering, namely magnetic resonance imaging and in particular diffusion MRI on one side, image processing and network theory o ...

When people interact to communicate, a very important role is played by the face. In fact, thanks to it we can get information about our interlocutors: who they are, what they feel, what their intentions are, etc. Studies demonstrated that facial expression is even more significant than verbal communication, and we can daily experience this in our life (when we want to tell something important to someone, we often prefer to have this person in front of us). This is why various researchers have been interest

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose a deep learning-based workflow for the evaluation of CRC lymph node me ...

A method that exploits an information theoretic framework to extract optimized audio features using video information is presented. A simple measure of mutual information (MI) between the resulting audio and video features allows the detection of the activ ...

Introduction Quantifying the myelin sheath radius of myelinated axons in vivo is important for understanding, diagnosing, and monitoring various neurological disorders. Despite advancements in diffusion MRI (dMRI) microstructure techniques, there are curre ...

Adverse conditions during fetal life have been associated to both structural and functional changes in neurodevelopment from the neonatal period to adolescence. In this study, connectomics was used to assess the evolution of brain networks from infancy to ...

Jean-Philippe Thiran

Chattez avec Graph Search

Hierarchical graph representations in digital pathology

Whole-brain structural connectivity in temporal lobe epilepsy: a Diffusion Spectrum Imaging study

Revisiting the T-2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Non-invasive pulmonary artery pressure estimation by electrical impedance tomography in a controlled hypoxemia study in healthy subjects

Microstructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue

Diversity of Cortico-descending Projections: Histological and Diffusion MRI Characterization in the Monkey

ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

Characterizing the connectome in schizophrenia with diffusion spectrum imaging

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Robust dimensionality reduction for interferometric imaging of Cygnus A

Submillimeter T-1 atlas for subject-specific abnormality detection at 7T

Laplacian Operator, Diffusion Flow and Active Contour on non-Euclidean Images

A Variational Model for Object Segmentation Using Boundary Information, Statistical Shape Prior and the Mumford-Shah Functional

Structural connectomics in brain diseases

Modelling human perception of static expressions by discrete choice models

Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model

Extraction of audio features specific to speech production for multimodal speaker detection

A diffusion MRI model for random walks confined on cylindrical surfaces: towards non-invasive quantification of myelin sheath radius

Structural Brain Network Reorganization and Social Cognition Related to Adverse Perinatal Condition from Infancy to Early Adolescence