Thomas Grenier
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View article: A generative adversarial optimization strategy for predicting counterfactual trajectories of grey matter atrophy
A generative adversarial optimization strategy for predicting counterfactual trajectories of grey matter atrophy Open
This study introduces a novel counterfactual generation method that provides interpretable, anatomically grounded explanations of MS progression. The framework serves as a powerful tool for hypothesis generation and model validation in bio…
View article: Impact of Long‐Term Fasting on Skeletal Muscle: Structure, Energy Metabolism and Function Using <sup>31</sup>P/<sup>1</sup>H MRS and MRI
Impact of Long‐Term Fasting on Skeletal Muscle: Structure, Energy Metabolism and Function Using <sup>31</sup>P/<sup>1</sup>H MRS and MRI Open
Background Fasting shows promise for public health, but concerns about muscle loss hinder its acceptance, particularly among the elderly. We explored the impact of long‐term fasting (12 days, 250 kcal/day) on muscle structure, metabolism a…
View article: Twelve Years of LabEx PRIMES (2012-2024)
Twelve Years of LabEx PRIMES (2012-2024) Open
An overview of the research performed in the Auvergne Rhône Alpes Region within theLaboratoire d’Excellence Physics, Radiobiology, Medical Imaging, and Simulation
View article: Comparative analysis of three advanced deep learning algorithms for Multiple Sclerosis lesion segmentation in FLAIR MRI
Comparative analysis of three advanced deep learning algorithms for Multiple Sclerosis lesion segmentation in FLAIR MRI Open
International audience
View article: Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D diffusion models
Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D diffusion models Open
Purpose: Bone metastasis have a major impact on the quality of life of patients and they are diverse in terms of size and location, making their segmentation complex. Manual segmentation is time-consuming, and expert segmentations are subj…
View article: Constrained non-negative networks for a more explainable and interpretable classification
Constrained non-negative networks for a more explainable and interpretable classification Open
International audience
View article: An unexpected confounder: how brain shape can be used to classify MRI scans ?
An unexpected confounder: how brain shape can be used to classify MRI scans ? Open
International audience
View article: CT-guided spatial normalization of nuclear hybrid imaging adapted to enlarged ventricles: Impact on striatal uptake quantification
CT-guided spatial normalization of nuclear hybrid imaging adapted to enlarged ventricles: Impact on striatal uptake quantification Open
The automatic CT-guided spatial normalization used herein led to a less biased spatial normalization of SPECT images, hence an improved semi-quantitative analysis. The proposed pipeline could be implemented in clinical routine to perform a…
View article: Pipeline for automatic segmentation of multiparametric MRI data in a rat model of ischemic stroke
Pipeline for automatic segmentation of multiparametric MRI data in a rat model of ischemic stroke Open
International audience
View article: Finite Element Models with Automatic Computed Tomography Bone Segmentation for Failure Load Computation
Finite Element Models with Automatic Computed Tomography Bone Segmentation for Failure Load Computation Open
Bone segmentation is an important step to perform biomechanical failure load simulations on in-vivo CT data of patients with bone metastasis, as it is a mandatory operation to obtain meshes needed for numerical simulations. Segmentation ca…
View article: Multiple sclerosis clinical forms classification with graph convolutional networks based on brain morphological connectivity
Multiple sclerosis clinical forms classification with graph convolutional networks based on brain morphological connectivity Open
Multiple Sclerosis (MS) is an autoimmune disease that combines chronic inflammatory and neurodegenerative processes underlying different clinical forms of evolution, such as relapsing-remitting, secondary progressive, or primary progressiv…
View article: Long-term follow-up of a LPC animal model using Optimal control MRI contrast targeting short T2 components
Long-term follow-up of a LPC animal model using Optimal control MRI contrast targeting short T2 components Open
International audience
View article: A Weakly Supervised Gradient Attribution Constraint for Interpretable Classification and Anomaly Detection
A Weakly Supervised Gradient Attribution Constraint for Interpretable Classification and Anomaly Detection Open
The lack of interpretability of deep learning reduces understanding of what happens when a network does not work as expected and hinders its use in critical fields like medicine, which require transparency of decisions. For example, a heal…
View article: PET image enhancement using artificial intelligence for better characterization of epilepsy lesions
PET image enhancement using artificial intelligence for better characterization of epilepsy lesions Open
Introduction [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) brain PET is used clinically to detect small areas of decreased uptake associated with epileptogenic lesions, e.g., Focal Cortical Dysplasias (FCD) but its performance is limited due to s…
View article: Impact of MR sequences choice on deep learning segmentation of muscles
Impact of MR sequences choice on deep learning segmentation of muscles Open
International audience
View article: Pesticide-Free Robotic Control of Aphids as Crop Pests
Pesticide-Free Robotic Control of Aphids as Crop Pests Open
Because our civilization has relied on pesticides to fight weeds, insects, and diseases since antiquity, the use of these chemicals has become natural and exclusive. Unfortunately, the use of pesticides has progressively had alarming effec…
View article: Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats
Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats Open
Thoracic radiograph (TR) is a complementary exam widely used in small animal medicine which requires a sharp analysis to take full advantage of Radiographic Pulmonary Pattern (RPP). Although promising advances have been made in deep learni…
View article: A Machine Learning pipeline to track the dynamics of a population of nanoparticles during in situ Environmental Transmission Electron Microscopy in gases
A Machine Learning pipeline to track the dynamics of a population of nanoparticles during in situ Environmental Transmission Electron Microscopy in gases Open
International audience
View article: Multiple Object Tracking of Supported Nanoparticles during in situ Environmental TEM Studies of Nanocatalysts
Multiple Object Tracking of Supported Nanoparticles during in situ Environmental TEM Studies of Nanocatalysts Open
International audience
View article: A More Interpretable Classifier For Multiple Sclerosis
A More Interpretable Classifier For Multiple Sclerosis Open
International audience
View article: Quantitative Magnetic Resonance Imaging Assessment of the Quadriceps Changes during an Extreme Mountain Ultramarathon
Quantitative Magnetic Resonance Imaging Assessment of the Quadriceps Changes during an Extreme Mountain Ultramarathon Open
Introduction/Purpose Extreme ultra-endurance races are growing in popularity, but their effects on skeletal muscles remain mostly unexplored. This longitudinal study explores physiological changes in mountain ultramarathon athletes’ quadri…
View article: LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography
LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography Open
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semiautomatically in clinical routine and is, thus, prone to interobserver and intraobserver varia…
View article: LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography Open
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semi-automatically in clinical routine, and is thus prone to inter- and intra-observer variability…
View article: A Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images
A Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images Open
In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convo…