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Jean-Philippe Thiran

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Publications associées (496)

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

Jean-Philippe Thiran, Manana Lortkipanidze, Guillaume Marc Georges Vray, Seyedbehzad Bozorgtabar, Devavrat Tomar

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 ...

Institute of Electrical and Electronics Engineers2021

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA

Jean-Philippe Thiran, Reto Meuli, Tobias Kober, Alessandro Daducci, Tom Hilbert, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato

Purpose Although several MRI methods have been explored to achievein vivomyelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the ...

Wiley2021

CLaiMS-Net: cortical lesions assessment in multiple sclerosis patients via a convolutional neural network and a single 3T MRI acquisition

Jean-Philippe Thiran, Meritxell Bach Cuadra, Cristina Granziera, Po-Jui Lu, Muhamed Barakovic, Francesco La Rosa

SAGE PUBLICATIONS LTD2021

Probing myelin content of the human brain with MRI: A review

Jean-Philippe Thiran, Tobias Kober, Tom Hilbert, Gian Franco Piredda

Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases o ...

WILEY2021

The Microstructural Features of the Diffusion-Simulated Connectivity (DiSCo) Dataset

Jean-Philippe Thiran, Gabriel Girard, Jonathan Rafael Patino Lopez, Marco Pizzolato

We present a detailed description of the structural characteristics of the MICCAI 2021 Diffusion Simulated Connectivity (DiSCo) Challenge synthetic dataset. The DiSCo dataset are one of a kind numerical phantoms for the simulation of the diffusion-weighted ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Beekeeping - artificial neural networks to fight varroa

Jean-Philippe Thiran, Mohammad Saeed Rad, Christian Robert Abbet, Maxime Camille Bohnenblust, Roser Vinals Terres, Alain Bugnon

AGRARFORSCHUNG2021

The Brain Connectome after Gamma Knife Radiosurgery of the Ventro-Intermediate Nucleus for Tremor: Marseille-Lausanne Radiobiology Study Protocol

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Constantin Tuleasca

Essential tremor (ET) is the most common movement disorder. Deep brain stimulation is the current gold standard for drug-resistant tremor, followed by radiofrequency lesioning. Stereotactic radiosurgery by Gamma Knife (GK) is considered as a minimally inva ...

2021

Learning Whole-Slide Segmentation from Inexact and Incomplete Labels Using Tissue Graphs

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

Segmenting histology images into diagnostically relevant regions is imperative to support timely and reliable decisions by pathologists. To this end, computer-aided techniques have been proposed to delineate relevant regions in scanned histology slides. Ho ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

The diffusion-simulated connectivity (DiSCo) dataset

Jean-Philippe Thiran, Gabriel Girard, Jonathan Rafael Patino Lopez, Marco Pizzolato

The methodological development in the mapping of the brain structural connectome from diffusion-weighted mag-netic resonance imaging (DW-MRI) has raised many hopes in the neuroscientific community. Indeed, the knowledge of the connections between different ...

ELSEVIER2021

A Registration Method for Three-Dimensional Analysis of Bone Mineral Density in the Proximal Tibia

Jean-Philippe Thiran, Brigitte Jolles-Haeberli

Although alterations in bone mineral density (BMD) at the proximal tibia have been suggested to play a role in various musculoskeletal conditions, their pathophysiological implications and their value as markers for diagnosis remain unclear. Improving our ...

2021

T-1 relaxometry abnormalities in white matter tracts predict functional systems scores in MS

Jean-Philippe Thiran, Bénédicte Marie Maréchal, Tobias Kober, Tom Hilbert

SAGE PUBLICATIONS LTD2021

Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images

Jean-Philippe Thiran, Mohammad Saeed Rad, Seyedbehzad Bozorgtabar, Thomas Yu

Existing reference (RF)-based super-resolution (SR) models try to improve perceptual quality in SR under the assumption of the availability of high-resolution RF images paired with low-resolution (LR) inputs at testing. As the RF images should be similar i ...

IEEE COMPUTER SOC2021

Automated detection of cortical lesions with single and multi-contrast 7T MRI

Jean-Philippe Thiran, Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa

SAGE PUBLICATIONS LTD2021

Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon

Solomzi Makohliso, Klaus Benedikt Schönenberger, Jean-Philippe Thiran, Roser Vinals Terres

Introduction ...

PUBLIC LIBRARY SCIENCE2021

HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification

Jean-Philippe Thiran, Guillaume Jaume

Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function relationship, have l ...

Springer Nature2020

Adaptive phase correction of diffusion-weighted images

Jean-Philippe Thiran, Maxime Descoteaux, Marco Pizzolato

Phase correction (PC) is a preprocessing technique that exploits the phase of images acquired in Magnetic Resonance Imaging (MRI) to obtain real-valued images containing tissue contrast with additive Gaussian noise, as opposed to magnitude images which fol ...

2020

SALAD: Self-Supervised Aggregation Learning for Anomaly Detection on X-Rays

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Seyedbehzad Bozorgtabar

2020

Axon morphology is modulated by the local environment and impacts the noninvasive investigation of its structure-function relationship

Jean-Philippe Thiran, Jonathan Rafael Patino Lopez, Tim Bjørn Dyrby

Axonal conduction velocity, which ensures efficient function of the brain network, is related to axon diameter. Noninvasive, in vivo axon diameter estimates can be made with diffusion magnetic resonance imaging, but the technique requires three-dimensional ...

National Academy of Sciences2020

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Jean-Philippe Thiran, Reto Meuli, Tobias Kober, Tom Hilbert

Purpose MP2RAGE T-1-weighted imaging has been shown to be beneficial for various applications, mainly because of its good grey-white matter contrast, its B-1-robustness and ability to derive T(1)maps. Even using parallel imaging, the method requires long a ...

WILEY2020

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

Jean-Philippe Thiran, Cristina Granziera, Alessandro Daducci, Muhamed Barakovic, Erick Jorge Canales Rodriguez

At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. Whil ...

2020

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