| Towards a coherent statistical framework for dense deformable template estimation S Allassonnière, Y Amit, A Trouvé Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2007 | 273 | 2007 |
| Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical … I Rekik, S Allassonnière, TK Carpenter, JM Wardlaw NeuroImage: Clinical 1 (1), 164-178, 2012 | 148 | 2012 |
| Construction of bayesian deformable models via a stochastic approximation algorithm: a convergence study S Allassonnière, E Kuhn, A Trouvé | 141 | 2010 |
| Learning spatiotemporal trajectories from manifold-valued longitudinal data JB Schiratti, S Allassonniere, O Colliot, S Durrleman Advances in neural information processing systems 28, 2015 | 88 | 2015 |
| Sparse adaptive parameterization of variability in image ensembles S Durrleman, S Allassonnière, S Joshi International Journal of Computer Vision 101, 161-183, 2013 | 72 | 2013 |
| A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations JB Schiratti, S Allassonnière, O Colliot, S Durrleman The Journal of Machine Learning Research 18 (1), 4840-4872, 2017 | 65 | 2017 |
| Geodesic shooting and diffeomorphic matching via textured meshes S Allassonnière, A Trouvé, L Younes Energy Minimization Methods in Computer Vision and Pattern Recognition: 5th …, 2005 | 49 | 2005 |
| Tumor growth parameters estimation and source localization from a unique time point: Application to low-grade gliomas I Rekik, S Allassonnière, O Clatz, E Geremia, E Stretton, H Delingette, ... Computer Vision and Image Understanding 117 (3), 238-249, 2013 | 40 | 2013 |
| Spatiotemporal propagation of the cortical atrophy: Population and individual patterns I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonniere, ... Frontiers in neurology 9, 235, 2018 | 34 | 2018 |
| Stochastic algorithm for bayesian mixture effect template estimation S Allassonnière, E Kuhn ESAIM: Probability and Statistics 14, 382-408, 2010 | 34* | 2010 |
| Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonnière, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 33 | 2017 |
| Bayesian mixed effect atlas estimation with a diffeomorphic deformation model S Allassonnière, S Durrleman, E Kuhn SIAM Journal on Imaging Sciences 8 (3), 1367-1395, 2015 | 28 | 2015 |
| AD Course Map charts Alzheimer’s disease progression I Koval, A Bône, M Louis, T Lartigue, S Bottani, A Marcoux, ... Scientific Reports 11 (1), 1-16, 2021 | 26 | 2021 |
| Convergent Stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation S Allassonniere, E Kuhn Computational Statistics & Data Analysis 91, 4-19, 2015 | 25 | 2015 |
| A stochastic algorithm for probabilistic independent component analysis S Allassonniere, L Younes | 24 | 2012 |
| Data augmentation in high dimensional low sample size setting using a geometry-based variational autoencoder C Chadebec, E Thibeau-Sutre, N Burgos, S Allassonnière IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 22 | 2022 |
| A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data JB Schiratti, S Allassonniere, A Routier, ... Information Processing in Medical Imaging: 24th International Conference …, 2015 | 21 | 2015 |
| Statistical models for deformable templates in image and shape analysis S Allassonnière, J Bigot, JA Glaunès, F Maire, FJP Richard Annales mathématiques Blaise Pascal 20 (1), 1-35, 2013 | 19 | 2013 |
| Map estimation of statistical deformable templates via nonlinear mixed effects models: Deterministic and stochastic approaches S Allassonnière, E Kuhn, A Trouvé 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, 80-91, 2008 | 17 | 2008 |
| Learning the clustering of longitudinal shape data sets into a mixture of independent or branching trajectories V Debavelaere, S Durrleman, S Allassonnière, ... International Journal of Computer Vision 128, 2794-2809, 2020 | 16 | 2020 |
Stanley DurrlemanInria, Paris Brain Institute (ICM)Bestätigte E-Mail-Adresse bei inria.fr
