Clinica is a software platform for multimodal brain image analysis in clinical research studies. It makes it easy to apply advanced analysis tools to large scale clinical studies. For that purpose, it integrates a comprehensive set of processing tools for the main neuroimaging modalities: currently MRI (anatomical, functional, diffusion) and PET, in the future, EEG/MEG.
For each modality, Clinica allows to easily extract various types of features (regional measures, parametric maps, surfaces, curves, networks). Such features are then subsequently used as input of machine learning, statistical modeling, morphometry or network analysis methods.


  • Routier, A., Guillon, J., Burgos, N., Samper-Gonzalez, J., Wen, J., Fontanella, S., Bottani, S., Jacquemont, T., Marcoux, A., Gori, P., Lu, P., Moreau, T., Bacci, M., Durrleman, S., Colliot, O. Clinica: an open source software platform for reproducible clinical neuroscience studies. In OHBM 2018. PDF Paper in PDF
  • Routier A, Marcoux A, Diaz Melo M, Guillon J, Samper-González J, Wen J, Bottani S, Guyot A, Thibeau-Sutre E, Teichmann M, Habert M-O, Durrleman S, Burgos N, Colliot O: New Advances in the Clinica Software Platform for Clinical Neuroimaging Studies. In OHBM 2019. PDF Paper in PDF
  • Routier A, Marcoux A, Diaz Melo M, Samper-González J, Wild A, Guyot A, Wen J, Thibeau- Sutre E, Bottani S, Durrleman S, Burgos N, Colliot O: New Longitudinal and Deep Learning Pipelines in the Clinica Software Platform. In OHBM, 2020. PDF Paper in PDF
  • Samper-González J, Burgos N, Bottani S, Fontanella S, Lu P, Marcoux A, Routier A, Guillon J, Bacci M, Wen J, Bertrand A, Bertin H, Habert MO, Durrleman S, Evgeniou T, Colliot O. Reproducible evaluation of classification methods in Alzheimer’s disease: Framework and application to MRI and PET data. Neuroimage, 183: 504–521, 2018. PDF Paper in PDF
  • Wen J, Thibeau-Sutre E, Samper-González J, Routier A, Bottani S, Durrleman S, Burgos N, Colliot O: Convolutional Neural Networks for Classification of Alzheimer’s Disease: Overview and Reproducible Evaluation, Medical Image Analysis, 63: 101694, 2020 PDF Paper in PDF
  • Marcoux A, Burgos N, Bertrand A, Teichmann M, Routier A, Wen J, Samper-González J, Bottani S, Durrleman S, Habert M-O, Colliot O: An Automated Pipeline for the Analysis of PET Data on the Cortical Surface. Frontiers in Neuroinformatics, 12, 2018. PDF Paper in PDF




Deformetrica is a software for the statistical analysis of 2D and 3D shape data. It essentially computes deformations of the 2D or 3D ambient space, which, in turn, warp any object embedded in this space, whether this object is a curve, a surface, a structured or unstructured set of points, or any combination of them.


  • S. Durrleman, S., Prastawa, M., Charon, N., Korenberg, J.R., Joshi, S., Gerig, G., Trouvé, A. Morphometry of anatomical shape complexes with dense deformations and sparse parameters.. In Neuroimage 101(1): 35-49, 2014 PDF Paper in PDF
  • Bône, A., Louis, M., Martin, B., & Durrleman, S. Deformetrica 4: an open-source software for statistical shape analysis. In nternational Workshop on Shape in Medical Imaging Springer, Cham, 2018. p. 3-13. PDF Paper in PDF


Brain network toolbox


A list of MATLAB routines for characterizing brain network topology though graph theoretical indices can be found at the website of the FreeBorN consortium, which promotes the interaction and visibility of the research teams studying brain connectivity and network theory.


To come soon

  • Schiratti J-B, Allassonniere S, Colliot O, Durrleman S.A Bayesian mixed-efects model to learn trajectories of changes from repeated manifold-valued observations. In Journal of Machine Learning Research (JMLR) 18(1), 4840-4872. 2017. PDF Paper in PDF
  • Koval I, Schiratti JB, Routier A, Bacci M, Colliot M, Allassonnière S, Durrleman S. Spatiotemporal propagation of the cortical atrophy: population and individual patterns. In Frontiers in Neurology 9, 2018. PDF Paper in PDF