Published in Imaging Neuroscience, 2025
A disease progression modeling approach for detecting sub-trajectories, applied to Alzheimer’s disease.
Published in Computational Statistics, 2024
Bayesian clustering and model selection approach for longitudinal data mixtures with exact finite-sample guarantees.
Published in Medical Image Analysis, 2024
A method for privacy-preserving medical image registration in federated settings.
Published in Multiple Sclerosis Journal, 2024
Review and application of AI methods for MRI data analysis in multiple sclerosis.
Published in Proceedings of the National Academy of Sciences, 2024
Study of inhibitory interneuron dynamics preceding epileptic seizures.
Published in Current Medical Imaging, 2024
MRI volumetric analysis of the hippocampus in early-onset schizophrenia.
Published in Brain Communications, 2024
Data-driven modeling of disability progression trajectories in progressive multiple sclerosis.
Published in Journal of Machine Learning Research, 2023
Theoretical study of tail decay rate estimation for loss function distributions in deep learning.
Published in NeuroImage, 2023
A multi-channel recurrent variational autoencoder for multimodal disease progression modeling in Alzheimer’s disease.
Published in Journal of Machine Learning Research, 2022
Unified convergence theory for federated optimization accommodating asynchronous and heterogeneous client updates.
Published in Journal of Machine Learning for Biomedical Imaging (MELBA), 2022
Differentially private probabilistic model for federated analysis of heterogeneous multi-view biomedical datasets.
Published in Nature Machine Intelligence, 2022
Deep learning approach predicting myocardial infarction risk from retinal fundus photographs and minimal clinical data.
Published in American Journal of Ophthalmology, 2022
Deep learning ensemble to predict visual fields from OCT data in glaucoma.
Published in Neurobiology of Aging, 2022
A dynamical model enabling personalized simulation and staging of Alzheimer’s disease progression.
Published in Frontiers in Molecular Medicine, 2022
Bayesian sparse regression model associating genetic data to multiple phenotypic features through biologically inspired constraints.
Published in Medical Image Analysis, 2021
An efficient active learning framework for vessel annotation and segmentation in medical images.
Published in Medical Image Analysis, 2021
A robust method for joint registration of histological stains and MRI for 3D reconstruction.
Published in Ophthalmology Glaucoma, 2021
Deep learning approach for enhancing optical coherence tomography signal quality.
Published in Medical Image Analysis, 2021
GAN-based data augmentation to improve statistical power in glaucoma clinical trials.
Published in NeuroImage, 2021
A Gaussian process progression model for learning protein propagation dynamics in neurodegeneration.
Published in Medical Image Analysis, 2021
Integration of biophysical modeling and statistical learning for heart-brain interaction analysis.
Published in Brain Communications, 2021
A computational model to simulate and predict the outcome of amyloid-targeting treatments in Alzheimer’s disease.
Published in Neurology Genetics, 2021
Spatiotemporal modeling of structural MRI changes across the Huntington disease timeline.
Published in NeuroImage, 2020
A monotonic Gaussian process model for spatiotemporal disease progression in neuroimaging.
Published in Neurobiology of Aging, 2020
Voxel-based analysis of longitudinal brain changes in response to multidomain preventive interventions.
Published in NeuroImage, 2019
Spatiotemporal shape analysis for detecting pre-symptomatic brain changes in genetic frontotemporal dementia.
Published in NeuroImage, 2019
DIVE: a spatiotemporal model estimating regional ordering and timing of brain pathology progression.
Published in NeuroImage, 2019
Statistical model disentangling aging and Alzheimer’s disease effects on brain morphology from cross-sectional data.
Published in eLife, 2019
Data-driven comparison of topological disease progression patterns across neurodegenerative diseases.
Published in Proceedings of the National Academy of Sciences, 2018
Imaging genetics analysis identifying TRIB3 as a susceptibility gene for brain atrophy in Alzheimer’s disease.
Published in Brain, 2018
GWAS of a multimodal imaging-based Alzheimer’s disease progression score identifies novel genetic loci.
Published in NeuroImage, 2018
Construction of a multi-atlas for MRI-based brain analysis in neonatal rabbits.
Published in NeuroImage, 2017
Gaussian Process Progression Model (GPPM) for probabilistic disease staging and biomarker trajectory estimation in Alzheimer’s disease.
Published in NeuroImage: Clinical, 2017
Analysis of selection bias in Alzheimer's disease classification pipelines and its impact on reported performance metrics.
Published in NeuroImage, 2017
Biophysical model of brain deformation for simulating longitudinal MRI changes in Alzheimer’s disease.
Published in Scientific Reports, 2016
Statistical model for multimodal neuroimaging analysis in Alzheimer's disease using non-local intensity correlations.
Published in Frontiers in Neuroscience, 2016
Computational framework for longitudinal image time series analysis using diffeomorphic deformations.
Published in Neurobiology of Aging, 2015
Statistical model to separate normal aging from Alzheimer’s disease-specific brain changes in MRI.
Published in NeuroImage, 2015
Regional flux analysis method to discover and quantify longitudinal anatomical changes in Alzheimer’s disease.
Published in NeuroImage, 2015
Comparative evaluation of brain atrophy measurement algorithms in dementia from the MIRIAD challenge.
Published in Psychiatry Research: Neuroimaging, 2014
MRI investigation of the impact of alcohol consumption on brain structure in healthy adults.
Published in Journal of Mathematical Imaging and Vision, 2014
Efficient algorithms for parallel transport of diffeomorphic deformations along geodesics, comparing Schild's and Pole Ladder schemes.
Published in Psychiatry Research: Neuroimaging, 2013
Comparative MRI study of structural brain differences in borderline personality disorder and bipolar disorder.
Published in International Journal of Computer Vision, 2013
Theoretical framework for geodesics, parallel transport, and one-parameter subgroups in the context of diffeomorphic image registration.
Published in NeuroImage, 2013
LCC-Demons: symmetric diffeomorphic image registration based on the Local Correlation Coefficient similarity measure.
Published in Drugs and Aging, 2011
fMRI study of the effect of memantine on default mode network activity in Alzheimer's disease.
Published in Dementia and Geriatric Cognitive Disorders, 2010
PET study of metabolic compensation mechanisms and their relationship with depression in Alzheimer's disease.
Published in Neurobiology of Aging, 2010
Strategy for patient enrichment using biomarkers in clinical trials for Alzheimer's disease in MCI patients.
Published in Neurology, 2009
PET-based in vivo mapping of amyloid-beta toxicity and its regional effects on brain function in Alzheimer's disease.
Published in International Conference on Machine Learning (ICML 2025), 2025
Analysis of computational complexity trade-offs in machine unlearning algorithms.
Published in 19th International Conference on Availability, Reliability and Security (ARES 2024), 2024
Scalable federated learning protocol robust to straggler clients through adaptive dropping strategies.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2024), 2024
Federated learning framework for multi-centric medical image segmentation addressing uneven label distributions across sites.
Published in International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2024
SIFU: a sequential federated unlearning method with provable guarantees for efficient client data removal.
Published in Neural Information Processing Systems (NeurIPS 2022), Datasets and Benchmarks Track, 2022
FLamby: a benchmark suite of realistic cross-silo federated learning datasets from healthcare domains.
Published in International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI (FL-IJCAI 2022), 2022
Theoretical framework unifying client sampling strategies in federated learning with convergence guarantees.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022), 2022
Privacy-preserving image registration method for federated medical imaging, presented at MICCAI 2022.
Published in International Conference on Machine Learning (ICML 2021), 2021
Clustered sampling strategy for client selection in federated learning, reducing variance and improving representativity.
Published in Information Processing in Medical Imaging (IPMI 2021), 2021
Probabilistic framework for modeling inter-site variability across federated biomedical datasets.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2021), 2021
Phase-independent latent representation for cardiac shape analysis across the cardiac cycle.
Published in International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 2020
Analysis of free-rider attacks in federated learning where malicious clients exploit aggregation without contributing.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2020), 2020
Combined data imputation and biophysical modelling to simulate heart-brain interactions in datasets with missing data.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2019), 2019
GAN-based OCT signal enhancement to improve statistical power in glaucoma clinical trials.
Published in Information Processing in Medical Imaging (IPMI 2019), 2019
Spatio-temporal model for inferring protein propagation dynamics across brain networks in neurodegeneration.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
Transfer learning approach for sharing disease knowledge across different neurodegenerative conditions.
Published in International Conference on Machine Learning (ICML 2019), 2018
Multi-Channel Variational Autoencoder (MCVAE) for joint latent representation learning from heterogeneous multimodal data using variational dropout for sparse encoding.
Published in International Conference on Machine Learning (ICML 2018), 2018
Framework for constraining the dynamics of deep probabilistic models, with application to disease progression modeling via gradient matching.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018), 2018
Model-based approach for refining nonlinear registrations in 3D histology reconstruction from serial sections.
Published in Information Processing in Medical Imaging (IPMI 2017), 2017
Vertex clustering model for spatiotemporal disease progression applied to cortical thickness in Alzheimer's disease.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016), 2016
Multi-modal spectral matching approach for longitudinal analysis of cortical development in preterm infants.
Published in Information Processing in Medical Imaging (IPMI 2015), 2015
Riemannian framework for intrinsic shape comparison and analysis of closed genus-zero surfaces.
Published in Information Processing in Medical Imaging (IPMI 2015), 2015
Gaussian process framework for efficient modelling and prediction of longitudinal image time series.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014), 2014
Biophysical model of brain shape deformation driven by atrophy in Alzheimer's disease.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2013
Sparse decomposition method for analyzing volume changes encoded in diffeomorphic deformation fields.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2012
Regional flux analysis applied to longitudinal brain atrophy in Alzheimer’s disease.
Published in Information Processing in Medical Imaging (IPMI), 2011
Schild’s ladder scheme for parallel transport of diffeomorphic deformations along geodesics in image time series.
Published in Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2011
Mapping the influence of amyloid-beta on longitudinal brain changes in healthy aging using diffeomorphic methods.
Published in 5th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DCL 2024), 2024
Secure aggregation protocol enhancing privacy guarantees in federated learning for healthcare.
Published in PharML Workshop at AAAI 2023, 2023
Benchmark study evaluating cost-effectiveness of federated and collaborative learning for prostate segmentation.
Published in NeurIPS 2023 Workshop on Diffusion Models, 2023
Parallel score matching method for faster training of diffusion models with improved density estimation.
Published in NeurIPS 2023 Workshop on Deep Learning and Differential Equations (DLDE-III), 2023
Augmented neural ODE architectures for improved density estimation in normalizing flows.
Published in Europace, 2022
Compact atrial shape representation for predicting thrombosis risk in atrial fibrillation.
Published in Europace, 2022
Novel image-based Scar Maturation Score for assessing long-term cardiac remodelling and arrhythmia risk after myocardial infarction.
Published in IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2022), 2022
Analysis of partial least squares methods for imaging genetics studies in Alzheimer's disease.
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2021), 2021
Multivariate analysis of brain microstructure and cognitive impairment in multiple sclerosis.
Published in Statistical Atlases and Computational Models of the Heart (STACOM 2020), 2020
Cross-sectional estimation of imaging biomarker progression in post-myocardial infarction patients.
Published in 1st MICCAI Workshop on Distributed and Collaborative Learning (DCL 2020), 2020
Introduction of Fed-BioMed, an open-source framework for federated learning in healthcare applications.
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice, 2019
Federated multivariate learning for meta-analysis of large-scale subcortical brain imaging data across distributed databases.
Published in Functional Imaging and Modeling of the Heart (FIMH 2019), 2019
Large-scale personalisation of a cardiovascular biophysical model for studying heart-brain interactions.
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice, 2018
One of the first applications of federated learning to medical imaging: meta-analysis of subcortical brain structures across distributed datasets.
Published in 12th International Symposium on Medical Information Processing and Analysis (SIPAIM 2017), 2017
Privacy-preserving multivariate online learning for large-scale multi-centric imaging genetics analysis.
Published in IEEE International Symposium on Biomedical Imaging (ISBI 2016), 2016
Partial least squares approach for imaging genetics analysis in Alzheimer's disease, evaluating plausibility and generalization.
Published in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2016), 2016
Efficient exponential approximation for integrating large velocity fields with application to diffeomorphic image registration.
Published in 1st ICML Workshop on Machine Learning Meets Medical Imaging, 2015
Gaussian process convolution model for non-stationary spatio-temporal changes in neurodegeneration.
Published in Geometric Science of Information (GSI 2013), 2013
Pole Ladder scheme for parallel transport of diffeomorphic deformations, applied to time series of images.
Published in MICCAI Workshop on Novel Imaging Biomarkers for Alzheimer's Disease (NIBAD 2012), 2012
Probabilistic flux analysis for detecting and quantifying longitudinal cerebral atrophy patterns.
Published in 3rd MICCAI Workshop on Mathematical Foundations of Computational Anatomy (MFCA 2011), 2011
Workshop contribution on geodesics and parallel transport for diffeomorphic image registration.
Published in MICCAI Workshop on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA 2010), 2010
4D diffeomorphic registration framework for serial brain MRI providing robust measures of longitudinal changes in Alzheimer's disease.
Published in arXiv preprint arXiv:2602.14938, 2026
Variance-reduced machine unlearning algorithm using forget-set gradients with (ε,δ)-privacy guarantees.
Published in arXiv (preprint), 2026
A federated framework for batch effect harmonization across collaborative imaging studies.
Published in arXiv preprint arXiv:2512.11878, 2025
Policy blueprint outlining technical requirements for trustworthy decentralized AI systems.
Published in arXiv preprint arXiv:2508.10343, 2025
Scalable framework for modeling nonlinear propagation dynamics across brain networks in neurodegeneration.
Published in arXiv preprint arXiv:2412.06494, 2024
Empirical analysis of the cost-effectiveness of federated and collaborative AI in real-world medical imaging settings.
Published in arXiv preprint arXiv:2309.07352, 2023
CLUB-PLS: a dimensionality reduction approach for high-dimensional imaging genetics analysis.
Published in arXiv preprint arXiv:2304.08054, 2023
Federated missing data imputation using deep generative models, extending MIWAE to the federated setting.
Published in arXiv preprint arXiv:1808.06367, 2018
Independent Gaussian process model for staging and characterizing spatio-temporal brain changes in Alzheimer’s disease.
Published in arXiv preprint arXiv:1701.01668, 2017
Random effect Gaussian process model for disease progression, introducing patient-specific time transformations to align individual trajectories.
Published in Federated Learning Systems, 2nd ed. (Springer, Studies in Computational Intelligence, vol. 832), 2025
Fed-BioMed: an open-source federated learning framework designed for real-world healthcare and biomedical applications.
Published in Medical Image Analysis (Elsevier, 2nd ed.), eds. Frangi, Prince, Sonka, 2023
Book chapter on imaging genetics methods, covering multivariate approaches for linking genetic variation to brain imaging phenotypes.
Published in Machine Learning for Brain Disorders (Springer), 2023
Book chapter on methods for multimodal data integration in brain disorder research.
Published in Riemannian Geometric Statistics in Medical Image Analysis (Elsevier), eds. Pennec, Sommer, Fletcher, 2020
Theoretical framework extending Riemannian geometry to affine connection settings for transformation groups in medical image analysis.
Published in Geometric Theory of Information Signals and Communication Technology (Springer), ed. Nielsen, 2014
Discrete ladder algorithms for parallel transport in transformation groups equipped with an affine connection structure.