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Jean-Philippe Thiran

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Publications associées (496)

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

Jean-Philippe Thiran, Alessandro Daducci, Muhamed Barakovic, Maxime Descoteaux

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 ...

AMER ASSOC ADVANCEMENT SCIENCE2020

Single-Shot CNN-Based Ultrasound Imaging with Sparse Linear Arrays

Jean-Philippe Thiran, Dimitris Perdios, Florian Martinez, Marcel Arditi, Manuel Vonlanthen

Sparse arrays are a topic of high interest within the ultrasound (US) imaging community, because of their promising ability to reduce costs, complexity, energy consumption, and data transfer requirements of US systems, thus addressing the main challenges o ...

IEEE2020

Quantitative brain relaxation atlases for personalized detection and characterization of brain pathology

Jean-Philippe Thiran, Reto Meuli, Guillaume Bonnier, Tobias Kober, Cristina Granziera, Tom Hilbert, Gian Franco Piredda

Purpose To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for long ...

WILEY2020

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Jean-Philippe Thiran, Muhamed Barakovic, Gabriel Girard, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Diffusion MRI (DW-MRI) allows for the detailed exploration of the brain white matter microstructure, with applications in both research and the clinic. However, state-of-the-art methods for microstructure estimation suffer from known limitations, such as t ...

Springer Nature2020

Topological principles and developmental algorithms might refine diffusion tractography

Jean-Philippe Thiran, Giorgio Innocenti, Alessandro Daducci, Gabriel Girard, Maxime Descoteaux, Tim Bjørn Dyrby

The identification and reconstruction of axonal pathways in the living brain or “ex-vivo” is promising a revolution in connectivity studies bridging the gap from animal to human neuroanatomy with extensions to brain structural–functional correlates. Unfort ...

2019

Sparse wars: A survey and comparative study of spherical deconvolution algorithms for diffusion MRI

Jean-Philippe Thiran, David Paul Roger Romascano, Alessandro Daducci, Muhamed Barakovic, Gabriel Girard, Gaëtan Olivier D Rensonnet, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Marco Pizzolato

Spherical deconvolution methods are widely used to estimate the brain's white-matter fiber orientations from diffusion MRI data. In this study, eight spherical deconvolution algorithms were implemented and evaluated. These included two model selection tech ...

2019

Noninvasive measurement of stroke volume changes in critically ill patients by means of electrical impedance tomography

Jean-Philippe Thiran, Mathieu Lemay, Martin Proença, Fabian Braun

Previous animal experiments have suggested that electrical impedance tomography (EIT) has the ability to noninvasively track changes in cardiac stroke volume (SV). The present study intended to reproduce these findings in patients during a fluid challenge. ...

SPRINGER HEIDELBERG2020

Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T

Jean-Philippe Thiran, Meritxell Bach Cuadra, Elena Najdenovska, José Pedro Rebelo Ferreira Marques, João Pedro Forjaco Jorge, Daniel Gallichan, Constantin Tuleasca

The ventro-intermediate nucleus (Vim), as part of the motor thalamic nuclei, is a commonly used target in functional stereotactic neurosurgery for treatment of drug-resistant tremor. As it cannot be directly visualized on routinely used magnetic resonance ...

Nature Research2019

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Jean-Philippe Thiran

Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem is especially acute, where there is a severe class imbalance. We propose an ...

2019

Real-Time Textureless-Region Tolerant High-Resolution Depth Estimation System

Yusuf Leblebici, Jean-Philippe Thiran, Bilal Demir

This study presents a real-time depth estimation hardware system aiming to provide high-resolution depth data and to eliminate its noise on textureless regions without causing any interference problem by utilizing artificial pattern projection. The system ...

2019

Fast model-based T-2 mapping using SAR-reduced simultaneous multislice excitation

Jean-Philippe Thiran, Gunnar Krüger, Tobias Kober, José Pedro Rebelo Ferreira Marques, Tom Hilbert

Purpose To obtain whole-brain high-resolution T-2 maps in 2 minutes by combining simultaneous multislice excitation and low-power PINS (power independent of number of slices) refocusing pulses with undersampling and a model-based reconstruction. Methods A ...

WILEY2019

Exploring Factors for Improving Low Resolution Face Recognition

Jean-Philippe Thiran, Hazim Kemal Ekenel

State-of-the-art deep face recognition approaches report near perfect performance on popular benchmarks, e.g., Labeled Faces in the Wild. However, their performance deteriorates significantly when they are applied on low quality images, such as those acqui ...

IEEE2019

Letter: Deep Brain Stimulation of the Pedunculopontine Nucleus Area in Parkinson Disease: Magnetic Resonance Imaging- Based Anatomoclinical Correlations and Optimal Target

Jean-Philippe Thiran, Meritxell Bach Cuadra, Dimitri Nestor Alice Van De Ville, Elena Najdenovska, Constantin Tuleasca, Adrien Jean Régis Maurice Hilaire

OXFORD UNIV PRESS INC2019

A Physical Model of Non-stationary Blur in Ultrasound Imaging

Paul Hurley, Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Matthieu Martin Jean-André Simeoni, Marcel Arditi

Conventional ultrasound (US) imaging relies on delay-and-sum (DAS) beamforming which retrieves a radio- frequency (RF) image, a blurred estimate of the tissue reflectivity function (TRF). Despite the non-stationarity of the blur induced by propagation effe ...

2019

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel

Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expression recognition accuracy despite having small number of real training images. ...

IEEE2019

Model-based image reconstruction method

Adrien Besson, Jean-Philippe Thiran, Dimitris Perdios, Adrien Georges Jean Besson, Marcel Arditi

The present invention concerns a pulse wave image reconstruction method to be used for example in ultrasound imaging. The proposed method is based on an image measurement model and its adjoint operator. The proposed method introduces matrix-free formulatio ...

2019

A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres

Jean-Philippe Thiran, Bogdan Draganski

Purpose of review ...

LIPPINCOTT WILLIAMS & WILKINS2019

Resting-state functional MRI for functional neurosurgery: seeing the light?

Jean-Philippe Thiran, Meritxell Bach Cuadra, Dimitri Nestor Alice Van De Ville, Elena Najdenovska, Constantin Tuleasca

AMER ASSOC NEUROLOGICAL SURGEONS2019

Learn to synthesize and synthesize to learn

Jean-Philippe Thiran, Mohammad Saeed Rad, Hazim Kemal Ekenel, Seyedbehzad Bozorgtabar

Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation between any two image domains using a single attribute or require training data ...

2019

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

Jean-Philippe Thiran, Guillaume Jaume, Hazim Kemal Ekenel

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely ...

IEEE2019

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