Jean-Philippe Thiran

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Neuronavigation systems are usually subject to inaccuracy due to intraoperative changes like brain shift or tumor resection. In order to correct for these deformations a biomechanical model of the brain is proposed. Not only elastic tissues, but also fluids are modeled, since an important volume of the head contains cerebrospinal fluid, which does not behave like soft tissues. Unlike other approaches, we propose to solve the differential equations of the model by means of the boundary element method, which

6 The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structur ...

In this paper we tackle the problem of regularisation for inverse problems in single shell diffusion weighted image restoration. Our aim is to recover a high-resolution and denoised DWI signal, prior to any model fitting. The main contribution of our metho ...

The focus of this paper is on the recognition of single object behavior from monocular image sequences. The general literature trend is to perform behavior recognition separately after an initial phase of feature/attribute extraction. We propose a framework where behavior recognition is performed jointly with attribute extraction, allowing the two tasks to mutually improve their results. To this end, we express the joint recognition / extraction problem in terms of a probabilistic temporal model, allowing i

In multiple testing, a variety of control metrics of false positives have been introduced such as the Per Family Error Rate (PFER), Family-Wise Error Rate (FWER), the False Discovery Rate (FDR), the False Exceedence Rate (FER). In this talk, we present a comprehensive family of error rates together with a corresponding family of multiple testing procedures (MTP). Based on the needs of the problem at hand, the user can choose a particular member among these MTPs. The new error rate limits the number of false

By benefiting from perceptual losses, recent studies have improved significantly the performance of the super-resolution task, where a high-resolution image is resolved from its low-resolution counterpart. Although such objective functions generate near-ph ...

Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...

When performing a tractography experiment it is essential to know whether a reconstructed tract results from the diffusion signal itself or from some random effect or noise. In this study, we introduce a way to associate to every connection a confidence le ...

Several metrics have been proposed in ultrasound pulse-echo imaging to quantify local coherence, with the coherence factor being the most prominent example. However, the coherence factor does not differentiate losses of coherence caused by variations of sp ...

Mild traumatic brain injury (mTBI) is one of the most frequently diagnosed neurological disorders in emergency departments. Although there are established recommendations for the diagnosis and treatment in the acute stage, there is an on-going debate in wh ...

The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortic ...

Objective. Cardiac arrhythmias are a leading cause of mortality worldwide. Wearable devices based on photoplethysmography give the opportunity to screen large populations, hence allowing for an earlier detection of pathological rhythms that might reduce th ...

Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available. It is also a very challenging task mainly because of the lower amount of information in the visual articulati ...

[0001] To obtain a data-structure that is characteristic of a physical object, a computer receives (413) sensor-data ({{y}}|↓) from a sensor-array. the received sensor-data ({{y}}|↓) is - in spatial and temporal data arrangement - a sub-set of sensor-data of a reference sensor-array. the computer uses a neural network to enhance (433) the received sensor-data to enhanced sensor-data so that - in spatial and temporal data arrangement - the enhanced sensor-data correspond to the sensor-data of the referenc

In this paper we present a computer based approach to analysis of social interaction experiments for the diagnosis of autism spectrum disorders in young children of 6-18 months of age. We apply face detection on videos from a head-mounted wireless camera t ...

Purpose: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirma ...

Validation of image registration algorithms is a difficult task and open-ended problem, usually application-dependent. In this paper we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and ess ...

The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of eigenfaces to achieve a good classification rate and how to train the SVM for a good generalization. As the experimental evidence show, generally one needs less eigenfaces than usually considered. We will present different strategies for choosing the dimensi

Objectives: Contralesional brain connectivity plasticity was previously reported after stroke. This study aims at disentangling the biological mechanisms underlying connectivity plasticity in the uninjured motor network after an ischemic lesion. In particu ...

22q11.2 deletion syndrome (22q11DS) is associated with an increased susceptibility to develop schizophrenia. Despite a large body of literature documenting abnormal brain structure in 22q11DS, cerebral changes associated with brain maturation in 22q11DS remained largely unexplored. To map cortical maturation from childhood to adulthood in 22q11.2 deletion syndrome, we used cerebral MRI from 59 patients with 22q11DS, aged 6 to 40, and 80 typically developing controls; three year follow-up assessments were al

Jean-Philippe Thiran

Chat with Graph Search

Brain Shift Correction Based on a Boundary Element Biomechanical Model with Different Material Properties

Resting-brain functional connectivity predicted by analytic measures of network communication

A Novel Spatial-Angular Domain Regularisation Approach for Restoration of Diffusion MRI

A Probabilistic Temporal Model for Joint Attribute Extraction and Behavior Recognition

Scaled False Discovery Proportion and Related Error Metrics

SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

How much confidence do we have in a MRI tractography experiment?

Using Windowed Radon Transform to Measure Local Coherence Independently of Speed-of-Sound Variations in Plane-Wave Imaging

Diagnostic approaches to predict persistent post-traumatic symptoms after mild traumatic brain injury - a literature review

Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

The influence of cardiac arrhythmias on the detection of heartbeats in the photoplethysmogram: benchmarking open-source algorithms

Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System

Ultrasound imaging with beamforming from data that are enhanced by a neural network in the signal domain

Analysis of Head Mounted Wireless Camera Videos for Early Diagnosis of Autism

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

A Cross Validation Study of Deep Brain Stimulation Targeting: From Experts to Atlas-Based, Segmentation-Based and Automatic Registration Algorithms

Face Detection using SVM Trained in Eigenfaces Space

Quantitative Analysis of Myelin and Axonal Remodeling in the Uninjured Motor Network After Stroke

Deviant trajectories of cortical maturation in 22q11.2 deletion syndrome (22q11DS): A cross-sectional and longitudinal study