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Jean-Philippe Thiran

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Publications associées (496)

Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis

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

Objectives Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize micro ...

Springer Heidelberg2023

Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA) - II. Code and real data proof of concept

Jean-Philippe Thiran, Ming Jiang

In a companion paper, a faceted wideband imaging technique for radio interferometry, dubbed Faceted HyperSARA, has been introduced and validated on synthetic data. Building on the recent HyperSARA approach, Faceted HyperSARA leverages the splitting functio ...

OXFORD UNIV PRESS2023

CrOC: Cross-View Online Clustering for Dense Visual Representation Learning

Jean-Philippe Thiran, Thomas Grégoire Stegmüller, Seyedbehzad Bozorgtabar

Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Clustering mechanism (CrOC) to discove ...

Los Alamitos2023

Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

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

Purpose Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging ( ...

Wiley2023

Adaptive Similarity Bootstrapping for Self-Distillation based Representation Learning

Jean-Philippe Thiran, Thomas Grégoire Stegmüller, Seyedbehzad Bozorgtabar

Most self-supervised methods for representation learning leverage a cross-view consistency objective i.e. they maximize the representation similarity of a given image's augmented views. Recent work NNCLR goes beyond the cross- view paradigm and uses positi ...

Ieee Computer Soc2023

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Molecular Imaging with Aquaporin-Based Reporter Genes: Quantitative Considerations from Monte Carlo Diffusion Simulations

Jean-Philippe Thiran, Jonathan Rafael Patino Lopez, Rémy Marc M Gardier

Aquaporins provide a unique approach for imaging genetic activity in deep tissues by increasing the rate of cellular water diffusion, which generates a magnetic resonance contrast. However, distinguishing aquaporin signals from the tissue background is cha ...

Amer Chemical Soc2023

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

Jean-Philippe Thiran, Muhamed Barakovic, Erick Jorge Canales Rodriguez

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius o ...

FRONTIERS MEDIA SA2023

Abnormal Cardiac Rhythm Detection Based on Photoplethysmography Signals and a Recurrent Neural Network

Jean-Marc Vesin, Jean-Philippe Thiran

Wearable devices based on photoplethysmography (PPG) allow for the screening of large populations at risk of cardiovascular disease. While PPG has shown the ability to discriminate atrial fibrillation (AF)-the most common cardiac arrhythmia (CA)-versus nor ...

IEEE Computer Society2023

Computer vision-based algorithm to sUppoRt coRrect electrode placemeNT (CURRENT) for home-based electric non-invasive brain stimulation

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

Objective: Home-based non-invasive brain stimulation (NIBS) has been suggested as an adjunct treatment strategy for neuro-psychiatric disorders. There are currently no available solutions to direct and monitor correct placement of the stimulation electrode ...

2023

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

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

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Tes ...

Los Alamitos2023

Telecytologic diagnosis of cervical smears for triage of self-sampled human papillomavirus–positive women in a resource-limited setting: concept development before implementation

Jean-Philippe Thiran, Thomas Grégoire Stegmüller, Micol Murtas

Cytology is an option for triaging human papillomavirus (HPV)-positive women. The interpretation of cytologic slides requires expertise and financial resources that are not always available in resource-limited settings. A solution could be offered by manua ...

2023

AMAE: Adaptation of Pre-trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

Unsupervised anomaly detection in medical images such as chest radiographs is stepping into the spotlight as it mitigates the scarcity of the labor-intensive and costly expert annotation of anomaly data. However, nearly all existing methods are formulated ...

Springer International Publishing Ag2023

ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

Jean-Philippe Thiran, Thomas Grégoire Stegmüller, Antoine Jérôme Spahr, Seyedbehzad Bozorgtabar

Progress in digital pathology is hindered by high-resolution images and the prohibitive cost of exhaustive localized annotations. The commonly used paradigm to categorize pathology images is patch-based processing, which often incorporates multiple instanc ...

IEEE COMPUTER SOC2023

Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model

Jean-Philippe Thiran

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose a deep learning-based workflow for the evaluation of CRC lymph node me ...

ELSEVIER SCIENCE INC2023

3-D Freehand Ultrasound Calibration Using A Tissue-Mimicking Phantom With Parallel Wires

Jean-Philippe Thiran, Sandra Maria Marcadent

article describes a method used to calibrate 3-D freehand ultrasound systems based on phantoms with parallel wires forming two perpendicular planes, such as the usual general-purpose commercial phantoms. In our algorithm, the phantom pose is co-optimized w ...

ELSEVIER SCIENCE INC2023

Artificial Intelligence-Based Cervical Cancer Screening on Images Taken during Visual Inspection with Acetic Acid: A Systematic Review

Jean-Philippe Thiran, Roser Vinals Terres

Visual inspection with acetic acid (VIA) is one of the methods recommended by the World Health Organization for cervical cancer screening. VIA is simple and low-cost; it, however, presents high subjectivity. We conducted a systematic literature search in P ...

MDPI2023

A Comparative Study on Detecting Heart Beats in Photoplethysmography Signals in Presence of Various Cardiac Arrhythmias

Jean-Marc Vesin, Jean-Philippe Thiran

Cardiac arrhythmias present a significant global health concern. The advent of wearable devices utilizing photoplethysmography gives the opportunity to screen large populations, hence offering the potential for early detection of pathological rhythms and r ...

IEEE Computer Society2023

Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime

Jean-Philippe Thiran, Christian Robert Abbet, Thomas Grégoire Stegmüller, Seyedbehzad Bozorgtabar

Screening Papanicolaou test samples has proven to be highly effective in reducing cervical cancer-related mortality. However, the lack of trained cytopathologists hinders its widespread implementation in low-resource settings. Deep learning-assisted telecy ...

Pergamon-Elsevier Science Ltd2023

Cortical alterations after very preterm birth and the association with socio-emotional abilities from childhood to early adolescence

Jean-Philippe Thiran, Elda Fischi Gomez, Vanessa Siffredi

Very preterm birth (VPT;

2023

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