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Jean-Philippe Thiran

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Publications associées (496)

Mental Flow Estimation Through Wearable EEG

Jean-Philippe Thiran

Flow is a mental state experienced during holistic involvement in a certain task, and it is a factor that promotes motivation, development, and performance. A reliable and objective estimation of the flow is essential for moving away from the traditional s ...

IEEE2022

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

Jean-Philippe Thiran, Gabriel Girard, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Rémy Marc M Gardier, Juan Luis Villarreal Haro

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 ...

2022

Toward individualized medicine in stroke-The TiMeS project: Protocol of longitudinal, multi-modal, multi-domain study in stroke

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Olaf Blanke, Philip Egger, Sylvain Jean-François Harquel, Silvestro Micera, Nathalie Heidi Meyer, Elena Beanato, Valérie Rita Madeleine Zufferey, Gabriel Girard, Julia Brügger, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Philipp Johannes Koch, Estelle Emeline Raffin, Andéol Geoffroy Cadic-Melchior, Traian Popa, Pauline Menoud, Lisa Aïcha Mireille Julie Fleury

Despite recent improvements, complete motor recovery occurs in < 15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the preci ...

FRONTIERS MEDIA SA2022

Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform

Jean-Philippe Thiran

Designing Deep Neural Networks (DNNs) running on edge hardware remains a challenge. Standard designs have been adopted by the community to facilitate the deployment of Neural Network models. However, not much emphasis is put on adapting the network topolog ...

IEEE2022

Examining the synergistic effects of a cognitive control video game and a home-based, self-administered non-invasive brain stimulation on alleviating depression: the DiSCoVeR trial protocol

Jean-Philippe Thiran, Roser Vinals Terres, Friedhelm Christoph Hummel, Takuya Morishita, Rémy Marc M Gardier, Fabienne Windel

Enhanced behavioral interventions are gaining increasing interest as innovative treatment strategies for major depressive disorder (MDD). In this study protocol, we propose to examine the synergistic effects of a self-administered home-treatment, encompass ...

SPRINGER HEIDELBERG2022

First evidence on the utility of T-1 mapping of the optic nerve to investigate differences between MS and NMOSD

Jean-Philippe Thiran, Bénédicte Marie Maréchal, Tobias Kober, Tom Hilbert, Veronica Lily Ravano, Gian Franco Piredda

SAGE PUBLICATIONS LTD2022

Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Cristina Granziera, Francesco La Rosa, Maxence Charles F Wynen

The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progres ...

ELSEVIER SCI LTD2022

X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries

Klaus Benedikt Schönenberger, Hubert Blanchard, René Salathé, Jean-Philippe Thiran, Romain Sahli, Sébastien Emmanuel Blanc, Mario Andres Chavarria Varon, Matthias Hüser, Jérôme Schmid

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 ligh ...

2022

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Jean-Philippe Thiran, Mohammad Saeed Rad, Guillaume Marc Georges Vray, Seyedbehzad Bozorgtabar, Devavrat Tomar

In medical image segmentation, supervised deep networks' success comes at the cost of requiring abundant labeled data. While asking domain experts to annotate only one or a few of the cohort's images is feasible, annotating all available images is impracti ...

IEEE COMPUTER SOC2022

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

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

As distribution shifts are inescapable in realistic clinical scenarios due to inconsistencies in imaging protocols, scanner vendors, and across different centers, well-trained deep models incur a domain generalization problem in unseen environments. Despit ...

PMLR2022

Evaluating reproducibility and subject-specificity of microstructure-informed connectivity

Jean-Philippe Thiran, Tobias Kober, Elda Fischi Gomez, Tom Hilbert, Elena Beanato, Gabriel Girard, Julia Brügger, Gian Franco Piredda, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Philipp Johannes Koch, Erick Jorge Canales Rodriguez, Marco Pizzolato, Andéol Geoffroy Cadic-Melchior, Chang-Hyun Park

Tractography enables identifying and evaluating the healthy and diseased brain's white matter pathways from diffusion-weighted magnetic resonance imaging data. As previous evaluation studies have reported significant false-positive estimation biases, recen ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Hierarchical graph representations in digital pathology

Jean-Philippe Thiran, Guillaume Jaume

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 ...

ELSEVIER2022

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

Jean-Philippe Thiran, Tobias Kober, Elda Fischi Gomez, Alessandro Daducci, Tom Hilbert, Elena Beanato, Gabriel Girard, Julia Brügger, Gian Franco Piredda, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Philipp Johannes Koch, Erick Jorge Canales Rodriguez, Marco Pizzolato, Andéol Geoffroy Cadic-Melchior, Thomas Yu, Chang-Hyun Park

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 ...

2022

Axonal T2 estimation using the spherical variance of the strongly diffusion-weighted MRI signal

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Marco Pizzolato

In magnetic resonance imaging, the application of a strong diffusion weighting suppresses the signal contributions from the less diffusion-restricted constituents of the brain's white matter, thus enabling the estimation of the transverse relaxation time T ...

ELSEVIER SCIENCE INC2022

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI

Jean-Philippe Thiran, Francesco La Rosa

Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical Lesio ...

WILEY2022

Neuroimaging Harmonization Using cGANs: Image Similarity Metrics Poorly Predict Cross-Protocol Volumetric Consistency

Jean-Philippe Thiran, Bénédicte Marie Maréchal, Tobias Kober, Veronica Lily Ravano

Computer-aided clinical decision support tools for radiology often suffer from poor generalizability in multi-centric frameworks due to data heterogeneity. In particular, magnetic resonance images depend on a large number of acquisition protocol parameters ...

Springer International Publishing Ag2022

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

Jean-Philippe Thiran, Bénédicte Marie Maréchal, Tobias Kober, Tom Hilbert, Ricardo Alberto Corredor Jerez, Gian Franco Piredda

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 ...

WILEY2022

Annotation-efficient image anomaly detection

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

The present invention proposes a method for detecting anomalous or out-of-distribution images in a machine learning system (1) comprising a pre-training network with a first encoder, and an anomaly detection network with a second encoder. The system is fir ...

2022

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

Jean-Philippe Thiran, Christian Robert Abbet, Seyedbehzad Bozorgtabar

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this is ...

ELSEVIER2022

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Jean-Philippe Thiran, Elda Fischi Gomez, Gabriel Girard, Gaëtan Olivier D Rensonnet, Jonathan Rafael Patino Lopez, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI da ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

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