Olivier Colliot
Présentation
Research Director at CNRS Head of the ARAMIS Lab, a joint team between CNRS, Inria, Inserm and University Pierre and Marie Curie at the Paris Brain Institute (ICM), in co-direction with Stanley Durrleman. Homepage: https://www.aramislab.fr/perso/colliot/ Email: olivier.colliot@cnrs.fr
Domaines de recherche
Publications
Publications
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Comparing Longitudinal Preprocessing Pipelines for Brain Volume Consistency in T1-Weighted MRI Test-Retest ScansSPIE Medical Imaging 2026, Feb 2026, Vancouver, Canada |
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Étude de la qualité des IRM T1 et FLAIR de routine clinique au sein d'un entrepôt de données de santé de l'AP-HPIABM 2026 - Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Mar 2026, Lyon, France |
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Assessing the Efficacy of Artefact Synthesis and Transfer Learning for Quality Control in Clinical 3D FLAIR Brain MRISPIE Medical Imaging 2026, Feb 2026, Vancouver, Canada |
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Comparing foundation models and nnU-Net for segmentation of primary brain lymphoma on clinical routine post-contrast T1-weighted MRISPIE Medical Imaging, SPIE, Feb 2025, San Diego (CA), United States. pp.45, ⟨10.1117/12.3044679⟩ |
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Simulation d'artefacts pour le contrôle automatique de la qualité d'IRM cérébrales FLAIR en routine cliniqueColloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM 2025), Mar 2025, Nice, France |
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Some hidden traps of confidence intervals in medical image segmentation: coverage issuesBRIDGE 2025 - MICCAI Workshop Bridging Regulatory Science and Medical Imaging Evaluation, Sep 2025, Deajeon, South Korea |
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Clinica, an open-source software to facilitate neuroimaging studiesColloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM), Mar 2024, Grenoble, France |
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Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRISPIE Medical Imaging 2024: Image Processing, Feb 2024, San Diego (CA), United States. ⟨10.1117/12.3005781⟩ |
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Evaluation of pseudo-healthy reconstruction for anomaly detection in brain FDG PETMIDL 2024 - Medical Imaging with Deep Learning, Jul 2024, Paris, France |
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Confidence intervals uncovered: Are we ready for real-world medical imaging AI?MICCAI 2024 - 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2024, Marrakech, Morocco. pp.124-132, ⟨10.1007/978-3-031-72117-5_12⟩ |
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The intriguing effect of frequency disentangled learning on medical image segmentationMedical Imaging 2024, Feb 2024, San Diego, CA, United States. pp.49, ⟨10.1117/12.2692286⟩ |
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Automatic quality control of segmentation results using early epochs as data augmentation: application to choroid plexuses2024 SPIE Medical Imaging, Feb 2024, San Diego, United States. pp.44, ⟨10.1117/12.3006580⟩ |
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Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networksSPIE Medical Imaging, Feb 2024, San Diego, United States. ⟨10.1117/12.3004975⟩ |
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Border irregularity loss for automated segmentation of primary brain lymphomas on post-contrast MRISPIE Medical Imaging 2024, Feb 2024, San Diego, CA, United States |
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Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter HyperintensitiesMedical Imaging with Deep Learning - MIDL 2024, Jul 2024, Paris, France |
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Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learningSPIE Medical Imaging, Feb 2024, San Diego, United States. pp.519-524, ⟨10.1117/12.3006039⟩ |
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From Nipype to Pydra: a Clinica storyOHBM 2023 - Annual meeting of the Organization for Human Brain Mapping, Jul 2023, Montreal, Canada |
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Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approachesDeep Generative Models workshop at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Oct 2023, Vancouver, Canada |
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Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data WarehouseDART 2023 - 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, Oct 2023, Vancouver (BC), Canada. pp.84-93, ⟨10.1007/978-3-031-45857-6_9⟩ |
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Introducing Soft Topology Constraints in Deep Learning-based Segmentation using Projected Pooling LossSPIE Medical Imaging 2023, Feb 2023, San Diego, United States |
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Interpretable automatic detection of incomplete hippocampal inversions using anatomical criteriaSPIE Medical Imaging 2023, Feb 2023, San Diego (California), United States. pp.1-7, ⟨10.1117/12.2651427⟩ |
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How can data augmentation improve attribution maps for disease subtype explainability?SPIE Medical Imaging, Feb 2023, San Diego, United States |
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Simulation-based evaluation framework for deep learning unsupervised anomaly detection on brain FDG PETSPIE Medical Imaging, Feb 2023, San Diego, United States |
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How precise are performance estimates for typical medical image segmentation tasks?IEEE International Symposium on Biomedical Imaging (ISBI 2023), IEEE, Apr 2023, Cartagena de Indias, Colombia |
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Transfer learning from synthetic to routine clinical data for motion artefact detection in brain T1-weighted MRISPIE Medical Imaging 2023: Image Processing, Feb 2023, San Diego, United States |
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Advances in the Clinica software platform for clinical neuroimaging studiesOHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom |
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Axial multi-layer perceptron architecture for automatic segmentation of choroid plexus in multiple sclerosisSPIE Medical Imaging 2022, Feb 2022, San Diego, United States. ⟨10.1117/12.2612912⟩ |
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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processingOHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom |
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MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data setISBI 2022 - International Symposium on Biomedical Imaging, Mar 2022, Kolkata, India. ⟨10.1109/ISBI52829.2022.9761504⟩ |
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A multimodal variational autoencoder for estimating progression scores from imaging and microRNA data in rare neurodegenerative diseasesSPIE Medical Imaging 2022: Image Processing, Feb 2022, San Diego, California, United States. pp.376-382, ⟨10.1117/12.2607250⟩ |
Highlight on Computing disease progression scores using multimodal variational autoencoders trained with neuroimaging and microRNA dataJobim 2022 - Journées Ouvertes en Biologie, Informatique et Mathématiques, Jul 2022, Rennes, France |
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Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived modelsSPIE Medical Imaging 2022: Image Processing, Feb 2022, San Diego, United States. pp.576-582, ⟨10.1117/12.2608565⟩ |
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Segmentation of new multiple sclerosis lesions on FLAIR MRI using online hard example miningMICCAI-MSSEG-2 - 25th International Conference on Medical Image Computing and Computer Assisted Intervention - challenge on multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure, Sep 2021, Strasbourg, France |
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Intensity based Regions Of Interest (ROIs) preselection followed by Convolutional Neuronal Network (CNN) based segmentation for new lesions detection in Multiple SclerosisMICCAI 2021 MSSEG2 - 24th International Conference on Medical Image Computing and Computer Assisted Intervention - Challenge on multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure — MICCAI-MSSEG-2, Sep 2021, Strasbourg, France |
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Clinica: an open-source software platform for reproducible clinical neuroscience studiesMRI Together 2021 - A global workshop on Open Science and Reproducible MR Research, Dec 2021, Online, France |
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Association and prediction of phenotypic traits from neuroimaging data using a multi-component mixed model excluding the target vertexSPIE Medical Imaging 2021, Feb 2021, Virtual, United States. pp.10, ⟨10.1117/12.2581022⟩ |
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Linear Mixed Models Minimise False Positive Rate and Enhance Precision of Mass Univariate Vertex-Wise Analyse of Grey-MatterISBI 2020 - International Symposium on Biomedical Imaging, Apr 2020, Iowa City / Virtual, United States |
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A step-wise criterion to determine target control centrality in the aging brain networkNetSci 2020 - International School and Conference on Network Science, Sep 2020, Rome / Virtual, Italy |
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New longitudinal and deep learning pipelines in the Clinica software platformOHBM 2020 - Annual meeting of the Organization for Human Brain Mapping, Jun 2020, Montreal / Virtual, Canada |
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Multilevel Survival Analysis with Structured Penalties for Imaging Genetics dataSPIE Medical Imaging Conference, Feb 2020, Houston, United States |
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Learning joint shape and appearance representations with metamorphic auto-encodersMICCAI 2020 - 23rd International Conference on Image Computing and Computer Assisted Interventions, Oct 2020, Lima / Virtual, Peru |
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Visualization approach to assess the robustness of neural networks for medical image classificationSPIE Medical Imaging 2020, Feb 2020, Houston, United States. ⟨10.1117/12.2548952⟩ |
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Hierarchical modeling of Alzheimer's disease progression from a large longitudinal MRI data setVPH 2020 - Virtual Physiological Human 2020, Aug 2020, Paris / Virtual, France |
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How serious is data leakage in deep learning studies on Alzheimer’s disease classification?Organization for Human Brain Mapping (OHBM), Jun 2019, Roma, Italy |
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Conciliation of process description and molecular interaction networks using logical properties of ontologyJOBIM 2019 - Journées Ouvertes Biologie, Informatique et Mathématiques, Jul 2019, Nantes, France |
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Deciphering the progression of PET alterations using surface-based spatiotemporal modelingOHBM 2019 - Annual meeting of the Organization for Human Brain Mapping, Jun 2019, Rome, Italy |
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Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI2019 OHBM Annual Meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy |
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Learning low-dimensional representations of shape data sets with diffeomorphic autoencodersIPMI 2019 : Information Processing in Medical Imaging, Jun 2019, Hong-Kong, China |
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Auto-encoding meshes of any topology with the current-splatting and exponentiation layersGeometry Meets Deep Learning @ ICCV 2019, Oct 2019, Séoul, South Korea |
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Hierarchical modeling of Alzheimer's disease progression from a large longitudinal MRI data setOHBM 2019 - 25th Annual Meeting of the Organization for Human Brain Mapping, Jun 2019, Roma, Italy |
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How serious is data leakage in deep learning studies on Alzheimer's disease classification?2019 OHBM Annual meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy |
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Predicting progression to Alzheimer’s disease from clinical and imaging data: a reproducible studyOHBM 2019 - Organization for Human Brain Mapping Annual Meeting 2019, Jun 2019, Rome, Italy |
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New advances in the Clinica software platform for clinical neuroimaging studiesOHBM 2019 - Annual Meeting on Organization for Human Brain Mapping, Jun 2019, Roma, Italy. ⟨10.1016/j.neuroimage.2011.09.015⟩ |
Target controllability in genetic networks of macrophage activationNetsci 2019, May 2019, Burlington, United States |
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Predicting Impulse Control Disorders in Parkinson's Disease: A Challenging TaskInternational Congress of Parkinson's Disease and Movement Disorders, Sep 2019, Nice, France |
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Prediction of future cognitive scores and dementia onset in Mild Cognitive Impairment patientsOHBM 2019 - Organization for Human Brain Mapping Conference, Jun 2019, Rome, Italy |
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Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging dataSPIE Medical Imaging 2019, Feb 2019, San Diego, United States. ⟨10.1117/12.2512430⟩ |
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Structural, microstructural and metabolic alterations in Primary Progressive Aphasia variantsAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapore, Singapore |
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Three simple ideas for predicting progression to Alzheimer's disease8th International Workshop on Pattern Recognition in Neuroimaging, Jun 2018, Singapour, Singapore |
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Clinica: an open source software platform for reproducible clinical neuroscience studiesAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapore, Singapore |
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Reproducible evaluation of Alzheimer's Disease classification from MRI and PET dataAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore |
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Identification of Driver Nodes in Genetic Networks Regulating Macrophage ActivationConference on Complex Systems - CSS, Sep 2018, Thessaloniki, Greece |
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Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphismsCVPR 2018 - Computer Vision and Pattern Recognition 2018, Jun 2018, Salt Lake City, United States |
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Using diffusion MRI for classification and prediction of Alzheimer's Disease: a reproducible studyAAIC 2018 - Alzheimer's Association International Conference, Jul 2018, Chicago, United States |
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Comparison of DTI Features for the Classification of Alzheimer's Disease: A Reproducible StudyOHBM 2018 - Organization for Human Brain Mapping Annual Meeting, Jun 2018, Singapour, Singapore |
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Integrating ontological representation and reasoning into a disease map: application to Alzheimer's diseaseDMCM 2018 - 3rd Disease Maps Community Meeting, Jun 2018, Paris, France. pp.1-2 |
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Converting Alzheimer's disease map into a heavyweight ontology: a formal network to integrate dataDILS 2018 - 13th International Conference on Data Integration in the Life Sciences, Nov 2018, Hannover, Germany. pp.1-9 |
Identification of driver nodes in genetic networks regulating macrophage activationInternational School and Conference on Network Science (Netsci) 2018, Jun 2018, Paris, France |
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NODDI Highlights Promising New Markers In Presymptomatic C9orf72 CarriersOHBM 2018 - Organization for Human Brain Mapping Annual Meeting, Jun 2018, Singapour, Singapore |
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Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial TrainingMICCAI 2018 – 21st International Conference On Medical Image Computing & Computer Assisted Intervention, Sep 2018, Granada, Spain. ⟨10.1007/978-3-030-00931-1_59⟩ |
Conciliation of medicine systems disease maps and other molecular interaction networks using logical properties of ontologyData Integration in the Life Sciences 5DILS 2018), Nov 2018, Hannover, Germany |
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FLAIR MR Image Synthesis By Using 3D Fully Convolutional Networks for Multiple SclerosisISMRM-ESMRMB 2018 - Joint Annual Meeting, Jun 2018, Paris, France. pp.1-6 |
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A pipeline for the analysis of 18F-FDG PET data on the cortical surface and its evaluation on ADNIAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore |
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Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networksMedical Image Computing and Computer Assisted Intervention, Sep 2017, Quebec City, Canada |
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Étude quantitative des anomalies de signal flair de la substance blanche dans les pathologies neurodégénérativesSFNR 2017 - 44ème Congrès de la Société Française de Neuroradiologie, Mar 2017, Paris, France. pp.1, ⟨10.1016/j.neurad.2017.01.011⟩ |
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Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality PatternsComputational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop], Sep 2017, Quebec City, Canada |
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White Matter Fiber Segmentation Using Functional VarifoldsMFCA 2017 - 6th MICCAI workshop on Mathematical Foundations of Computational Anatomy, Sep 2017, Québec, Canada. pp.92-100 |
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Prediction of amyloidosis from neuropsychological and MRI data for cost effective inclusion of pre-symptomatic subjects in clinical trialsMultimodal Learning for Clinical Decision Support, Sep 2017, Quebec City, Canada |
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Multilevel Modeling with Structured Penalties for Classification from Imaging Genetics data3rd MICCAI Workshop on Imaging Genetics (MICGen 2017), Sep 2017, Québec City, Canada. pp.230-240 |
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Accuracy of MRI classification algorithms in a tertiary memory center clinical routine cohortAAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P772-P774, ⟨10.1016/j.jalz.2017.06.1034⟩ |
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Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's DiseaseMachine Learning in Medical Imaging 2017, Sep 2017, Quebec City, Canada. pp.8 |
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Early Diagnosis of Alzheimer’s Disease Using Subject-Specific Models of FDG-PET DataAAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.1-2, ⟨10.1016/j.jalz.2017.06.1618⟩ |
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Diagnosis of Alzheimer’s Disease Through Identification of Abnormality Patterns in FDG PET Data30th Annual Congress of the European Association of Nuclear Medicine (EANM), Oct 2017, Vienna, Austria. pp.253 - 254, ⟨10.1007/s00259-017-3822-1⟩ |
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Selection of amyloid positive pre-symptomatic subjects using automatic analysis of neuropsychological and MRI data for cost effective inclusion procedures in clinical trialsClinical Trials for Alzheimer's Disease, Nov 2017, Boston, United States. pp.295 |
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Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline6th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Sep 2017, Quebec City, Canada |
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Multi-modal analysis of genetically-related subjects using SIFT descriptors in brain MRIWorkshop on Computational Diffusion MRI, CDMRI 2017, MICCAI Workshop, Sep 2017, Quebec, Canada |
The INSIGHT cohort: baseline analysis of structural MR imaging in asymptomatic subjects at risk for Alzheimer's diseaseAAIC, Jul 2016, Toronto, Canada. ⟨10.1016/j.jalz.2016.06.612⟩ |
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Suspected non-alzheimer disease pathophysiology (SNAP) categorization in the insight cohortAAIC, 2016, Toronto, Canada. pp.P1073 - P1074, ⟨10.1016/j.jalz.2016.06.2246⟩ |
Imaging of hippocampal inner structure at 7T: robust in-vivo acquisition protocolAnnual Meeting of the Organization for Human Brain Mapping, OHBM 2015, 2015, Honolulu, United States |
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Segmentation of hippocampal inner structure using 7T in-vivo MRI: a robust anatomical protocolAnnual Meeting of the Organization for Human Brain Mapping, OHBM 2015, 2015, Honolulu, United States |
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Multi-template approaches for segmenting the hippocampus: the case of the SACHA softwareOrganization for Human Brain Mapping (OHBM), Jun 2015, Honolulu, United States. pp.5 |
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Learning spatiotemporal trajectories from manifold-valued longitudinal dataNeural Information Processing Systems, Dec 2015, Montréal, Canada |
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Unified analysis of shape and structural connectivity of neural pathwaysOrganisation for Human Brain Mapping, 2015, Honolulu, United States |
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A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data IPMI - Information Processing in Medical Imaging |
Statistical shape analysis of large datasets using diffeomorphic iterative centroidsHuman Brain Mapping - 2015, Jun 2015, Honolulu, United States |
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Measuring the thickness of the hippocampal pyramidal layer using in vivo 7T MRIAnnual Meeting of the Organization for Human Brain Mapping, OHBM 2015, 2015, Honolulu, United States |
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Joint Morphometry of Fiber Tracts and Gray Matter structures using Double DiffeomorphismsIPMI - Information Processing in Medical Imaging, Jun 2015, Isle of Skye, United Kingdom. pp.275-287, ⟨10.1007/978-3-319-19992-4_21⟩ |
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Characterization of Incomplete Hippocampal Inversions in a large dataset of young healthy subjectsHuman Brain Mapping - 2015, Jun 2015, Honolulu, United States |
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Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data5th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Oct 2015, Munich, Germany |
Slab registration as a first step towards hippocampus subparts high resolution imaging at 7TISMRM 2014 - Annual Meeting of the International Society for Magnetic Resonance in Medicine, May 2014, Milan, Italy |
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Genetic Frontotemporal Dementia with TDP-43 Inclusions:Distinct Radiological Phenotypes between Patients with PGRN and C9ORF72 MutationsRSNA, Nov 2014, Chicago, United States |
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Multimodal neuroimaging study in presymptomatic GRN mutations carriers9th International Conference on Frontotemporal Dementias (ICFTD), Oct 2014, Vancouver, Canada |
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A Prototype Representation to Approximate White Matter Bundles with Weighted CurrentsMICCAI 2014 - 17th International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2014, Boston, United States |
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Evaluation of morphometric descriptors of deep brain structures for the automatic classification of patients with Alzheimer’s disease, mild cognitive impairment and elderly controlsMICCAI Workshop, Sep 2014, Cambridge, United States. pp.8 |
Incidence and characterization of supratentorial FLAIR hyperintenstities in patients with sporadic and genetic frontotemporal dementiaAAIC 2014 - Alzheimer’s Association International Conference, Jul 2014, Copenhagen, Denmark |
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Improved accuracy of the diagnosis of early Alzheimer’s disease using combined measures of hippocampal volume and sulcal morphologyAAN 2014 - Annual Meeting of the American Academy of Neurology, Apr 2014, Philadelphia, United States |
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Fast Template-based Shape Analysis using Diffeomorphic Iterative CentroidMIUA 2014 - Medical Image Understanding and Analysis 2014, Jul 2014, Egham, United Kingdom. pp.39-44 |
Template Estimation for Large Database: A Diffeomorphic Iterative Centroid Method Using CurrentsGSI 2013 - First International Conference Geometric Science of Information, Aug 2013, Paris, France. pp.103-111, ⟨10.1007/978-3-642-40020-9_10⟩ |
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Towards joint morphometry of white matter tracts and gray matter surfacesHuman Brain Mapping, 2013, Seattle, United States |
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Bayesian Atlas Estimation for the Variability Analysis of Shape ComplexesMICCAI 2013 : Medical Image Computing and Computer Assisted Intervention, Sep 2013, Nagoya, Japan. pp.267-274, ⟨10.1007/978-3-642-40811-3_34⟩ |
Automatic segmentation of white matter hyperintensities robust to multicentre acquisition and pathological variabilitySPIE 2012 - Symposium on Medical Imaging, Feb 2012, San Diego, United States. pp.1-9, ⟨10.1117/12.910268⟩ |
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Segmentation of white matter hyperintensities: a comparison of automatic methods on multicentre dataOHBM 2012 - 18th Annual Meeting of the Organization for Human Brain Mapping, Jun 2012, Beijing, China |
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Modelling morphological variability of the hippocampus using manifold learning and large deformationsOHBM 2012 - 18th Annual Meeting of the Organization for Human Brain Mapping, Jun 2012, Pekin, China |
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T 1 mapping, AIF and Pharmacokinetic Parameter Extraction from Dynamic Contrast Enhancement MRI DataMICCAI Workshop on Multimodal Brain Image Analysis MBIA 2011, 2011, Toronto, Canada. pp.76 - 83, ⟨10.1007/978-3-642-24446-9_10⟩ |
Anatomical Regularization on Statistical Manifolds for the Classification of Patients with Alzheimer's DiseaseMICCAI Workshop on Machine Learning in Medical Imaging, Sep 2011, Toronto, Canada. pp.201-208, ⟨10.1007/978-3-642-24319-6_25⟩ |
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Automatic segmentation of age-related white matter changes on flair images: method and multicentre validationISBI 2011 - 8th IEEE International Symposium on Biomedical Imaging: from Nano to Macro, Mar 2011, Chicago, United States. pp.2014 - 2017, ⟨10.1109/ISBI.2011.5872807⟩ |
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Spatial and anatomical regularization of SVM for brain image analysisNeural Information Processing Systems NIPS 2010, 2010, Vancouver, Canada |
Automated segmentation of white matter lesions using FLAIR images.OHBM 2010 - 16th International Conference on Functional Mapping of the Human Brain, Jun 2010, Barcelona, Spain |
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Spatially Regularized SVM for the Detection of Brain Areas Associated with Stroke OutcomeMedical Image Computing and Computer-Assisted Intervention, MICCAI 2010, 2010, Beijing, China. pp.316 - 323, ⟨10.1007/978-3-642-15705-9_39⟩ |
DISCO: a coherent diffeomorphic framework for brain registration under exhaustive sulcal constraintsMedical Image Computing and Computer-Assisted Intervention - MICCAI 2009, Sep 2009, United Kingdom. pp.730-738 |
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Multi-Scale Diffeomorphic Cortical Registration Under Manifold Sulcal Constraints2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, May 2008, France. pp.1127-1130 |
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Improved segmentation of focal cortical dysplasia lesions on MRI using expansion towards cortical boundaries3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro (ISBI), 2006, Arlington, VA, USA, United States. pp.323-326 |
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Segmentation of Focal Cortical Dysplasia Lesions Using a Feature-Based Level SetProc. Medical Image Computing and Computer Assisted Intervention (MICCAI'05), 2005, Palm Springs (CA), USA, United States. pp.375-382, ⟨10.1007/1156646547⟩ |
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A level set driven by MR features of focal cortical dysplasia for lesion segmentationMedical Image Understanding and Analysis (MIUA), 2005, no address, United States. pp.239-242 |
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Integration of fuzzy structural information in deformable modelsInformation Processing and Management of Uncertainty IPMU 2004, 2004, Perugia, Italy |
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3D nonlinear PET-CT image registration algorithm with constrained Free-Form Deformations3rd IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP 2003), 2003, Benalmadena, Spain |
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Characterization of approximate plane symmetries for 3D fuzzy objects9th International Conference on Information Processing and Management of Uncertainty IPMU 2002), Jul 2002, Annecy, France. pp.1749-1756 |
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Brain symmetry plane computation in MR images using inertia axes and optimization16th International Conference on Pattern Recognition, Aug 2002, Québec, Canada. ⟨10.1109/ICPR.2002.1044783⟩ |
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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing3IA Doctoral Workshop, Nov 2021, Toulouse, France |
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Visualization approach to assess the robustness of neural networks for medical image classificationICM days 2019, Jan 2020, Louan, France |
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Identification of unlabeled latent subtypes with saliency mapsICM welcome days, Oct 2020, Paris (online), France |
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A log-logistic survival model from multimodal data for prediction of Alzheimer's DiseaseSAfJR 2019 - Survival Analysis for Junior Researchers, Apr 2019, Copenhague, Denmark |
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On the genetic bases of incomplete hippocampal inversion: a genome-wide association studyOHBM 2019 - Annual Meeting on Organization for Human Brain Mapping, Jun 2019, Rome, Italy. pp.1 |
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Building disease progression models from longitudinal biomarkers5th Annual Human Brain Project Summit, Oct 2017, Glasgow, United Kingdom |
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Learning spatio-temporal trajectories from manifold-valued longitudinal dataNeural Information Processing Systems, Dec 2015, Montréal, Canada. , Advances in Neural Information Processing Systems |
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Machine Learning for Brain DisordersOlivier Colliot. Springer, 197, 2023, Neuromethods, 978-1-0716-3195-9. ⟨10.1007/978-1-0716-3195-9⟩ |
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Reproducibility in medical image computing: what is it and how is it assessed?Marco Lorenzi and Maria Zuluaga. Trustworthy AI in Medical Imaging, Elsevier, pp.177-204, 2024, MICCAI Book Series, Elsevier, ⟨10.1016/B978-0-44-323761-4.00018-3⟩ |
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Machine learning for Parkinson’s disease and related disordersOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_26⟩ |
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Classic machine learning methodsOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023 |
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Evaluating machine learning models and their diagnostic valueOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023 |
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A non-technical introduction to machine learningOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023 |
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Deep learning: basics and convolutional neural networks (CNN)Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_3⟩ |
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Reproducibility in machine learning for medical imagingOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023 |
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Interpretability of Machine Learning Methods Applied to NeuroimagingOlivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_22⟩ |
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Biomarqueurs IRM de la maladie d’Alzheimer : apport du traitement des imagesTillement Jean-Paul; Hauw Jean-Jacques; Papadopoulos Vassilios. Vieillissement et démences : un défi médical, scientifique et socio-économique, Lavoisier, pp.25-37, 2014, Rapports de l’Académie Nationale de Médecine |
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Diffeomorphic Iterative Centroid Methods for Template Estimation on Large DatasetsFrank Nielsen. Geometric Theory of Information, Chapter 10, Springer, pp.273-299, 2014, ⟨10.1007/978-3-319-05317-2_10⟩ |
Devices for generation of synthetic 3D representations of myelin content (MyeliGAN)France, Patent n° : WO 2025/068000 A1. 2025 |
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Représentation, évaluation et utilisation de relations spatiales pour l'interprétation d'images. Application à la reconnaissance de structures anatomiques en imagerie médicaleInterface homme-machine [cs.HC]. Télécom ParisTech, 2003. Français. ⟨NNT : ⟩ |