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Jean-Philippe Thiran

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Related publications (496)

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020

Real-time high-resolution omnidirectional imaging platform for drone detection and tracking

Yusuf Leblebici, Jean-Philippe Thiran, Vladan Popovic, Selman Ergünay, Gökçen Nurlu, Bilal Demir

Drones have become steadily affordable, which raises privacy and security concerns as well as interest in drone detection systems. On the other hand, drone detection is a challenging task due to small dimensions of drones, difficulty of long-distance detec ...

SPRINGER HEIDELBERG2020

Editorial: Computational Pathology

Jean-Philippe Thiran, Inti Zlobec

2020

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

Jean-Philippe Thiran, Meritxell Bach Cuadra, Ahmed Abdulkadir, Cristina Granziera, Mario Joao Fartaria de Oliveira, Po-Jui Lu, Muhamed Barakovic, Francesco La Rosa

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 ...

2020

Structure Preserving Stain Normalization of Histopathology Images Using Self Supervised Semantic Guidance

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

2020

Normalization of aberrant pretherapeutic dynamic functional connectivity of extrastriate visual system in patients who underwent thalamotomy with stereotactic radiosurgery for essential tremor: a resting-state functional MRI study

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

OBJECTIVE The tremor circuitry has commonly been hypothesized to be driven by one or multiple pacemakers within the cerebello-thalamo-cortical pathway, including the cerebellum, contralateral motor thalamus, and primary motor cortex. However, previous stud ...

2020

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

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

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 ...

2020

Image reconstruction method based on a trained non-linear mapping

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

The present invention concerns an array processing image reconstruction method comprising: receiving (13) a set of echo waveforms as measurements from the object of interest; defining (15) a measurement model linking an unknown image of the object to the m ...

2020

Translating mprage to mp2rage improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Jean-Philippe Thiran, Thomas Yu, Francesco La Rosa

SAGE PUBLICATIONS LTD2020

X-ray imaging detector for radiological applications in the harsh environments of low-income countries

Klaus Benedikt Schönenberger, René Salathé, Jean-Philippe Thiran, Mario Andres Chavarria Varon

This paper describes the development of a novel medical X-ray imaging system adapted to the needs and constraints of low and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible light ...

2020

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

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

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 ...

NATURE RESEARCH2020

A comprehensive error rate for multiple testing

Stephan Morgenthaler, Jean-Philippe Thiran, Djalel Eddine Meskaldji, Dimitri Nestor Alice Van De Ville

Over the last two decades, a large variety of type I error rates and control procedures have been proposed in the field of multiple hypotheses testing. This paper proposes a framework that includes many existing proposals by investigating procedures in whi ...

SPRINGER2020

Quantitative t(1) deviations in brain lesions and nawm improve the clinico-radiological correlation in early ms

Jean-Philippe Thiran

SAGE PUBLICATIONS LTD2020

Divide-and-Rule: Self- Supervised Learning for Survival Analysis in Colorectal Cancer

Jean-Philippe Thiran, Christian Robert Abbet, Seyedbehzad Bozorgtabar, Inti Zlobec

2020

Model-based super-resolution reconstruction of T-2 maps

Jean-Philippe Thiran, Reto Meuli, Mohammad Golbabaee, Tobias Kober, Tom Hilbert, Gian Franco Piredda, Wajiha Bano

Purpose High-resolution isotropic T-2 mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2D sequence, the resolution is limited by the slice thickness. If used as a 3D acquisition, specific absorption rate ...

Wiley2020

Benefiting from Multitask Learning to Improve Single Image Super-Resolution

Jean-Philippe Thiran, Mohammad Saeed Rad, Claudiu-Cristian Musat, Hazim Kemal Ekenel

Despite significant progress toward super resolving more realistic images by deeper convolutional neural networks (CNNs), reconstructing fine and natural textures still remains a challenging problem. Recent works on single image super resolution (SISR) are ...

2020

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

Medical image segmentation is an important task forcomputer aided diagnosis. Pixelwise manual annotationsof large datasets require high expertise and is time consum-ing. Conventional data augmentations have limited benefitby not fully representing the unde ...

2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Elda Fischi Gomez, Cristina Granziera, Tom Hilbert, Muhamed Barakovic, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

ActiveAx(ADD): Toward non-parametric and orientationally invariant axon diameter distribution mapping using PGSE

Jean-Philippe Thiran, David Paul Roger Romascano, Alessandro Daducci, Muhamed Barakovic, Jonathan Rafael Patino Lopez, Tim Bjørn Dyrby

Purpose Non-invasive axon diameter distribution (ADD) mapping using diffusion MRI is an ill-posed problem. Current ADD mapping methods require knowledge of axon orientation before performing the acquisition. Instead, ActiveAx uses a 3D sampling scheme to e ...

Wiley2020

Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results

Jean-Philippe Thiran, David Paul Roger Romascano, Gabriel Girard, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Alonso Ramirez Manzanares

Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in the design of the biomimicking geometrical configurations ...

2020

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