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Stanley Durrleman
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2020 – today
- 2023
- [c49]Benoît Sauty, Stanley Durrleman:
Impact of sex and APOE-ε4 genotype on regional brain metabolism in Alzheimer's Disease. ISBI 2023: 1-5 - [c48]Nemo Fournier
, Stanley Durrleman
A Multimodal Disease Progression Model for Genetic Associations with Disease Dynamics. MICCAI (5) 2023: 601-610 - 2022
- [j34]Thomas Lartigue
Deterministic Approximate EM Algorithm; Application to the Riemann Approximation EM and the Tempered EM. Algorithms 15(3): 78 (2022) - [j33]Anupama Goparaju, Krithika Iyer, Alexandre Bône
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. Medical Image Anal. 76: 102271 (2022) - [c47]Benoît Sauty, Stanley Durrleman:
Riemannian Metric Learning for Progression Modeling of Longitudinal Datasets. ISBI 2022: 1-5 - [c46]Benoît Sauty, Stanley Durrleman:
Progression Models for Imaging Data with Longitudinal Variational Auto Encoders. MICCAI (1) 2022: 3-13 - [c45]Kristyna Manousková, Valentin Abadie, Mehdi Ounissi, Gabriel Jimenez, Lev Stimmer, Benoît Delatour, Stanley Durrleman, Daniel Racoceanu:
Tau protein discrete aggregates in Alzheimer's disease: neuritic plaques and tangles detection and segmentation using computational histopathology. Digital and Computational Pathology 2022 - 2021
- [j32]Clément Mantoux
Understanding the Variability in Graph Data Sets through Statistical Modeling on the Stiefel Manifold. Entropy 23(4): 490 (2021) - [j31]Alexandre Routier
Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies. Frontiers Neuroinformatics 15: 689675 (2021) - [j30]Paolo Piras, Valerio Varano
Transporting Deformations of Face Emotions in the Shape Spaces: A Comparison of Different Approaches. J. Math. Imaging Vis. 63(7): 875-893 (2021) - [j29]Manon Ansart, Stéphane Epelbaum
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review. Medical Image Anal. 67: 101848 (2021) - [j28]Junhao Wen
Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease. Neuroinformatics 19(1): 57-78 (2021) - [j27]Thomas Lartigue
Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 3196-3213 (2021) - [j26]Thomas Lartigue
Mixture of Conditional Gaussian Graphical Models for Unlabelled Heterogeneous Populations in the Presence of Co-factors. SN Comput. Sci. 2(6): 466 (2021) - [j25]Alexis Guyot, Ana B. Graciano Fouquier, Emilie Gerardin, Marie Chupin, Joan Alexis Glaunès, Linda Marrakchi-Kacem, Johanne Germain, Claire Boutet
A Diffeomorphic Vector Field Approach to Analyze the Thickness of the Hippocampus From 7 T MRI. IEEE Trans. Biomed. Eng. 68(2): 393-403 (2021) - [c44]Pierre-Emmanuel Poulet
Mixture Modeling for Identifying Subtypes in Disease Course Mapping. IPMI 2021: 571-582 - [c43]Raphaël Couronné, Paul Vernhet, Stanley Durrleman:
Longitudinal Self-supervision to Disentangle Inter-patient Variability from Disease Progression. MICCAI (2) 2021: 231-241 - [c42]Samuel Gruffaz, Pierre-Emmanuel Poulet, Etienne Maheux, Bruno Jedynak, Stanley Durrleman:
Learning Riemannian metric for disease progression modeling. NeurIPS 2021: 23780-23792 - 2020
- [j24]Vianney Debavelaere
Learning the Clustering of Longitudinal Shape Data Sets into a Mixture of Independent or Branching Trajectories. Int. J. Comput. Vis. 128(12): 2794-2809 (2020) - [j23]Alexandre Bône
Learning the spatiotemporal variability in longitudinal shape data sets. Int. J. Comput. Vis. 128(12): 2873-2896 (2020) - [j22]Junhao Wen
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation. Medical Image Anal. 63: 101694 (2020) - [j21]Wen Wei, Emilie Poirion, Benedetta Bodini, Matteo Tonietto
Predicting PET-derived myelin content from multisequence MRI for individual longitudinal analysis in multiple sclerosis. NeuroImage 223: 117308 (2020) - [c41]Alexandre Bône, Paul Vernhet, Olivier Colliot
Learning Joint Shape and Appearance Representations with Metamorphic Auto-Encoders. MICCAI (1) 2020: 202-211 - [i14]Thomas Lartigue
Gaussian Graphical Model exploration and selection in high dimension low sample size setting. CoRR abs/2003.05169 (2020) - [i13]Anupama Goparaju, Alexandre Bône, Nan Hu, Heath B. Henninger, Andrew E. Anderson, Stanley Durrleman, Matthijs Jacxsens, Alan Morris, Ibolya Csecs, Nassir Marrouche, Shireen Y. Elhabian:
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications. CoRR abs/2009.02878 (2020)
2010 – 2019
- 2019
- [j20]Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman
Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis. Medical Image Anal. 58 (2019) - [j19]Claire Cury
Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort. NeuroImage 188: 282-290 (2019) - [c40]Alexandre Bône
Auto-Encoding Meshes of any Topology with the Current-Splatting and Exponentiation Layers. ICCV Workshops 2019: 4014-4023 - [c39]Alexandre Bône
Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders. IPMI 2019: 195-207 - [c38]Maxime Louis, Raphaël Couronné, Igor Koval, Benjamin Charlier, Stanley Durrleman
Riemannian Geometry Learning for Disease Progression Modelling. IPMI 2019: 542-553 - [c37]Raphaël Couronné, Marie Vidailhet, Jean-Christophe Corvol, Stéphane Lehéricy, Stanley Durrleman:
Learning Disease Progression Models With Longitudinal Data and Missing Values. ISBI 2019: 1033-1037 - [c36]Vianney Debavelaere, Alexandre Bône
Clustering of Longitudinal Shape Data Sets Using Mixture of Separate or Branching Trajectories. MICCAI (4) 2019: 66-74 - [e5]Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec
Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11846, Springer 2019, ISBN 978-3-030-33225-9 [contents] - [i12]Igor Koval, Stéphanie Allassonnière
Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects. CoRR abs/1904.02921 (2019) - [i11]Junhao Wen, Elina Thibeau-Sutre
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation. CoRR abs/1904.07773 (2019) - 2018
- [j18]Arnaud Marcoux, Ninon Burgos
An Automated Pipeline for the Analysis of PET Data on the Cortical Surface. Frontiers Neuroinformatics 12: 94 (2018) - [j17]Jorge Samper-González, Ninon Burgos
Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data. NeuroImage 183: 504-521 (2018) - [j16]Barbara Gris, Stanley Durrleman, Alain Trouvé:
A Sub-Riemannian Modular Framework for Diffeomorphism-Based Analysis of Shape Ensembles. SIAM J. Imaging Sci. 11(1): 802-833 (2018) - [j15]Maxime Louis, Benjamin Charlier, Paul Jusselin, Susovan Pal
A Fanning Scheme for the Parallel Transport along Geodesics on Riemannian Manifolds. SIAM J. Numer. Anal. 56(4): 2563-2584 (2018) - [j14]Pietro Gori
Double Diffeomorphism: Combining Morphometry and Structural Connectivity Analysis. IEEE Trans. Medical Imaging 37(9): 2033-2043 (2018) - [c35]Maxime Louis, Benjamin Charlier, Stanley Durrleman:
Geodesic Discriminant Analysis for Manifold-Valued Data. CVPR Workshops 2018: 332-340 - [c34]Alexandre Bône
Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms. CVPR 2018: 9271-9280 - [c33]Alexandre Bône
Deformetrica 4: An Open-Source Software for Statistical Shape Analysis. ShapeMI@MICCAI 2018: 3-13 - [c32]Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman
Learning Myelin Content in Multiple Sclerosis from Multimodal MRI Through Adversarial Training. MICCAI (3) 2018: 514-522 - [e4]Stefan Klein, Marius Staring, Stanley Durrleman, Stefan Sommer
Biomedical Image Registration - 8th International Workshop, WBIR 2018, Leiden, The Netherlands, June 28-29, 2018, Proceedings. Lecture Notes in Computer Science 10883, Springer 2018, ISBN 978-3-319-92257-7 [contents] - [i10]Alexandre Bône, Olivier Colliot, Stanley Durrleman:
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms. CoRR abs/1803.10119 (2018) - [i9]Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, Olivier Colliot:
Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training. CoRR abs/1804.08039 (2018) - [i8]Jorge Samper-González, Ninon Burgos, Simona Bottani, Sabrina Fontanella, Pascal Lu, Arnaud Marcoux, Alexandre Routier, Jérémy Guillon, Michael Bacci, Junhao Wen, Anne Bertrand, Hugo Bertin, Marie Odile Habert, Stanley Durrleman, Theodoros Evgeniou, Olivier Colliot, Alzheimer's Disease Neuroimaging Initiative:
Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data. CoRR abs/1808.06452 (2018) - [i7]Junhao Wen, Jorge Samper-González, Simona Bottani, Alexandre Routier, Ninon Burgos
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease. CoRR abs/1812.11183 (2018) - 2017
- [j13]Jean-Baptiste Schiratti, Stéphanie Allassonnière, Olivier Colliot, Stanley Durrleman:
A Bayesian Mixed-Effects Model to Learn Trajectories of Changes from Repeated Manifold-Valued Observations. J. Mach. Learn. Res. 18: 133:1-133:33 (2017) - [j12]Pietro Gori
A Bayesian framework for joint morphometry of surface and curve meshes in multi-object complexes. Medical Image Anal. 35: 458-474 (2017) - [j11]James Fishbaugh, Stanley Durrleman, Marcel Prastawa
Geodesic shape regression with multiple geometries and sparse parameters. Medical Image Anal. 39: 1-17 (2017) - [c31]Maxime Louis, Alexandre Bône
Parallel Transport in Shape Analysis: A Scalable Numerical Scheme. GSI 2017: 29-37 - [c30]Ninon Burgos
Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns. CMMI/RAMBO/SWITCH@MICCAI 2017: 13-22 - [c29]Jorge Samper-González, Ninon Burgos
Yet Another ADNI Machine Learning Paper? Paving the Way Towards Fully-Reproducible Research on Classification of Alzheimer's Disease. MLMI@MICCAI 2017: 53-60 - [c28]Kuldeep Kumar
White Matter Fiber Segmentation Using Functional Varifolds. GRAIL/MFCA/MICGen@MICCAI 2017: 92-100 - [c27]Alexandre Bône
Prediction of the Progression of Subcortical Brain Structures in Alzheimer's Disease from Baseline. GRAIL/MFCA/MICGen@MICCAI 2017: 101-113 - [c26]Manon Ansart, Stéphane Epelbaum, Geoffroy Gagliardi
Prediction of Amyloidosis from Neuropsychological and MRI Data for Cost Effective Inclusion of Pre-symptomatic Subjects in Clinical Trials. DLMIA/ML-CDS@MICCAI 2017: 357-364 - [c25]Igor Koval, Jean-Baptiste Schiratti, Alexandre Routier, Michael Bacci, Olivier Colliot
Statistical Learning of Spatiotemporal Patterns from Longitudinal Manifold-Valued Networks. MICCAI (1) 2017: 451-459 - [e3]M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10551, Springer 2017, ISBN 978-3-319-67674-6 [contents] - [i6]Kuldeep Kumar, Pietro Gori, Benjamin Charlier, Stanley Durrleman, Olivier Colliot, Christian Desrosiers:
White Matter Fiber Segmentation Using Functional Varifolds. CoRR abs/1709.06144 (2017) - [i5]Jorge Samper-González, Ninon Burgos, Sabrina Fontanella, Hugo Bertin, Marie Odile Habert, Stanley Durrleman, Theodoros Evgeniou, Olivier Colliot:
Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease. CoRR abs/1709.07267 (2017) - [i4]Igor Koval, Jean-Baptiste Schiratti, Alexandre Routier, Michael Bacci, Olivier Colliot, Stéphanie Allassonnière, Stanley Durrleman:
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks. CoRR abs/1709.08491 (2017) - [i3]Alexandre Bône, Maxime Louis, Alexandre Routier, Jorge Samper-González, Michael Bacci, Benjamin Charlier, Olivier Colliot, Stanley Durrleman:
Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline. CoRR abs/1711.08716 (2017) - [i2]Maxime Louis, Alexandre Bône, Benjamin Charlier, Stanley Durrleman:
Parallel transport in shape analysis: a scalable numerical scheme. CoRR abs/1711.08725 (2017) - [i1]Olivier Colliot, Fabrizio de Vico Fallani, Stanley Durrleman:
Modelling Neurodegenerative Diseases from Multimodal Medical Images. ERCIM News 2017(108) (2017) - 2016
- [j10]Pietro Gori, Olivier Colliot
Parsimonious Approximation of Streamline Trajectories in White Matter Fiber Bundles. IEEE Trans. Medical Imaging 35(12): 2609-2619 (2016) - [c24]Jean Dumoncel
How to Build an Average Model When Samples are Variably Incomplete? Application to Fossil Data. CVPR Workshops 2016: 541-548 - [c23]Claire Cury
Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease. SeSAMI@MICCAI 2016: 63-75 - 2015
- [j9]Stéphanie Allassonnière
Bayesian Mixed Effect Atlas Estimation with a Diffeomorphic Deformation Model. SIAM J. Imaging Sci. 8(3): 1367-1395 (2015) - [c22]Barbara Gris, Stanley Durrleman, Alain Trouvé:
A Sub-Riemannian Modular Approach for Diffeomorphic Deformations. GSI 2015: 39-47 - [c21]Pietro Gori, Olivier Colliot
Joint Morphometry of Fiber Tracts and Gray Matter Structures Using Double Diffeomorphisms. IPMI 2015: 275-287 - [c20]Jean-Baptiste Schiratti, Stéphanie Allassonnière, Alexandre Routier, Olivier Colliot
A Mixed-Effects Model with Time Reparametrization for Longitudinal Univariate Manifold-Valued Data. IPMI 2015: 564-575 - [c19]Jean-Baptiste Schiratti, Stéphanie Allassonnière, Olivier Colliot, Stanley Durrleman:
Learning spatiotemporal trajectories from manifold-valued longitudinal data. NIPS 2015: 2404-2412 - [e2]Stanley Durrleman
Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data - Third International Workshop, STIA 2014, Held in Conjunction with MICCAI 2014, Boston, MA, USA, September 18, 2014, Revised Selected Papers. Lecture Notes in Computer Science 8682, Springer 2015, ISBN 978-3-319-14904-2 [contents] - 2014
- [j8]Stanley Durrleman
Morphometry of anatomical shape complexes with dense deformations and sparse parameters. NeuroImage 101: 35-49 (2014) - [c18]James Fishbaugh, Marcel Prastawa, Guido Gerig
Geodesic regression of image and shape data for improved modeling of 4D trajectories. ISBI 2014: 385-388 - [c17]Prasanna Muralidharan, James Fishbaugh, Hans J. Johnson
Diffeomorphic Shape Trajectories for Improved Longitudinal Segmentation and Statistics. MICCAI (3) 2014: 49-56 - [c16]Pietro Gori, Olivier Colliot
A Prototype Representation to Approximate White Matter Bundles with Weighted Currents. MICCAI (3) 2014: 289-296 - 2013
- [j7]Islem Rekik, Stéphanie Allassonnière
Spatiotemporal Dynamic Simulation of Acute Perfusion/Diffusion Ischemic Stroke Lesions Evolution: A Pilot Study Derived from Longitudinal MR Patient Data. Comput. Math. Methods Medicine 2013: 283593:1-283593:13 (2013) - [j6]Stanley Durrleman
Sparse Adaptive Parameterization of Variability in Image Ensembles. Int. J. Comput. Vis. 101(1): 161-183 (2013) - [j5]Stanley Durrleman
Toward a Comprehensive Framework for the Spatiotemporal Statistical Analysis of Longitudinal Shape Data. Int. J. Comput. Vis. 103(1): 22-59 (2013) - [c15]Alexandre Imperiale, Alexandre Routier, Stanley Durrleman
Improving Efficiency of Data Assimilation Procedure for a Biomechanical Heart Model by Representing Surfaces as Currents. FIMH 2013: 342-351 - [c14]James Fishbaugh, Marcel Prastawa
Geodesic Image Regression with a Sparse Parameterization of Diffeomorphisms. GSI 2013: 95-102 - [c13]James Fishbaugh, Marcel Prastawa
Geodesic Shape Regression in the Framework of Currents. IPMI 2013: 718-729 - [c12]Pietro Gori, Olivier Colliot
Bayesian Atlas Estimation for the Variability Analysis of Shape Complexes. MICCAI (1) 2013: 267-274 - 2012
- [c11]Anuja Sharma, Stanley Durrleman
Longitudinal growth modeling of discrete-time functions with application to DTI tract evolution in early neurodevelopment. ISBI 2012: 1397-1400 - [c10]Stanley Durrleman
Topology Preserving Atlas Construction from Shape Data without Correspondence Using Sparse Parameters. MICCAI (3) 2012: 223-230 - [c9]James Fishbaugh, Marcel Prastawa, Stanley Durrleman
Analysis of Longitudinal Shape Variability via Subject Specific Growth Modeling. MICCAI (1) 2012: 731-738 - [c8]James Fishbaugh, Stanley Durrleman
A framework for longitudinal data analysis via shape regression. Image Processing 2012: 83143K - [e1]Stanley Durrleman
Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data - Second International Workshop, STIA 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012. Proceedings. Lecture Notes in Computer Science 7570, Springer 2012, ISBN 978-3-642-33554-9 [contents] - 2011
- [j4]Stanley Durrleman
Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents. NeuroImage 55(3): 1073-1090 (2011) - [j3]Tommaso Mansi, Ingmar Voigt, Benedetta Leonardi, Xavier Pennec
A Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot. IEEE Trans. Medical Imaging 30(9): 1605-1616 (2011) - [c7]James Fishbaugh, Stanley Durrleman
Estimation of Smooth Growth Trajectories with Controlled Acceleration from Time Series Shape Data. MICCAI (2) 2011: 401-408 - 2010
- [b1]Stanley Durrleman:
Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution. (Modèles statistiques de courants pour mesurer la variabilité anatomique de courbes, de surfaces et de leur évolution). University of Nice Sophia Antipolis, France, 2010 - [c6]Vladlena Gorbunova, Stanley Durrleman
Lung CT registration combining intensity, curves and surfaces. ISBI 2010: 340-343
2000 – 2009
- 2009
- [j2]Stanley Durrleman
Statistical models of sets of curves and surfaces based on currents. Medical Image Anal. 13(5): 793-808 (2009) - [c5]Stanley Durrleman
A Statistical Model of White Matter Fiber Bundles Based on Currents. IPMI 2009: 114-125 - [c4]Tommaso Mansi, Stanley Durrleman
A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning. MICCAI (1) 2009: 214-221 - [c3]Stanley Durrleman
Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets. MICCAI (1) 2009: 297-304 - 2008
- [j1]Stanley Durrleman
Inferring brain variability from diffeomorphic deformations of currents: An integrative approach. Medical Image Anal. 12(5): 626-637 (2008) - [c2]Stanley Durrleman
Sparse Approximation of Currents for Statistics on Curves and Surfaces. MICCAI (2) 2008: 390-398 - 2007
- [c1]Stanley Durrleman
Measuring Brain Variability Via Sulcal Lines Registration: A Diffeomorphic Approach. MICCAI (1) 2007: 675-682
Coauthor Index
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