Publications

Books or Proceedings

  • S. Klein, M. Staring, S. Durrleman and S. Sommer, editors, Proceedings of Eight International Workshop on Biomedical Image Registration (WBIR'18, Leiden, The Netherlands),, Lecture Notes in Computer Science, Vol 10883
  • X. Pennec, S. Joshi, M. Nielsen, T. Fletcher, S. Durrleman and S. Sommer, editors, Proceedings of Sixth International Workshop on Mathematical Foundations of Computational Anatomy (MFCA'17, Quebec, Canada),, Lecture Notes in Computer Science, Vol 10551
  • X. Pennec, S. Joshi, M. Nielsen, T. Fletcher, S. Durrleman and S. Sommer, editors, Proceedings of Fifth International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Biological Shape Variability Modeling (MFCA'15, Munich, Germany), link
  • S. Durrleman, T. Fletcher, G. Gerig, M. Niethammer, X. Pennec, editors, Proceedings of Third International Workshop on Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'14, Boston, USA), Lecture Notes in Computer Science (LNCS), Vol. 8682, ISBN 978-3-319-14905-9, link
  • X. Pennec, S. Joshi, M. Nielsen, T. Fletcher, S. Durrleman and S. Sommer, editors, Proceedings of Fourth International Workshop on Methematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Biological Shape Variability Modeling (MFCA'13, Nagoya, Japan), link
  • S. Durrleman, T. Fletcher, G. Gerig and M. Niethammer, editors, Proceedings of Second International Workshop on Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12, Nice, France), Lecture Notes in Computer Science (LNCS), Vol. 7570, ISBN 978-3-642-33555-6, link

Thesis

  • S. Durrleman Geometrical Approaches in Statistical Learning for the Construction of Digital Models of the Human Brain, University Pierre and Marie Curie, June 2018, pdf
  • S. Durrleman Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution, University of Nice-Sophia Antipolis, March 2010, pdf, Second Gilles Kahn Award for best dissertation in Computer Science (2010) press release (english) (french)

Articles in Journals or Book Chapters

  • M. Ansart, S. Epelbaum, G, Gagliardi, O. Colliot, D. Dormont, B. Dubois, H. Hampel, S. Durrleman, Reduction of recruitment costs in preclinical AD trials. Validation of automatic pre-screening algorithm for brain amyloidosis, Statistical Methods in Medical Research, 2019, link
  • J. Wen, H. Zhang, D. C Alexander, S. Durrleman, A. Routier, D. Rinaldi, M. Houot, Ph. Couratier, D. Hannequin, F. Pasquier, J. Zhang, O. Colliot, I. Le Ber, A. Bertrand, Neurite density is reduced in the presymptomatic phase of C9orf72 disease, J Neurol Neurosurg Psychiatry, 2018
  • C. Cury, S. Durrleman, et al. , Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort, Neuroimage, 2018 (to appear)
  • A. Marcoux, N. Burgos, A. Bertrand, M. Teichmann, A. Routier, J. Wen, J. Samper-Gonzalez, S. Bottani, S. Durrleman, M.-O. Habert, and O. Colliot, An Automated Pipeline for the Analysis of PET Data on the Cortical Surface, Frontiers in Neuroinformatics, Frontiers in Neuroinformatics, 2018, link
  • J. Samper-Gonzalez, N. Burgos, S. Bottani, S. Fontanella, P. Lu, A. Marcoux, A. Routier, J. Guillon, M. Bacci, J. Wen, A. Bertrand, H. Bertin, M.-O. Habert, S. Durrleman, Theodoros Evgeniou, Olivier Colliot, Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data, NeuroImage, Vol. 183, 504-521, 2018
  • M. Louis, B. Charlier, P. Jusselin, S. Pal, and S. Durrleman, A Fanning Scheme for the Parallel Transport Along Geodesics on Riemannian Manifolds,SIAM Journal on Numerical Analysis 56 (4), 2563-2584, 2018
  • I. Koval, J.-B. Schiratti, A. Routier, M. Bacci, O. Colliot, S. Allassonnière, S. Durrleman, Spatiotemporal propagation of the cortical atrophy during the course of Alzheimer’s Disease : Population and individual patterns,Frontiers in Neurology, Vol 9, p 235, 2018
  • H. Hampel, N. Toschi, C. Babiloni, F. Baldacci, K.L. Black, A.L.W. Bokde, R.S. Bun, F. Cacciola, E. Cavedo, P.A. Chiesa, O. Colliot, C.M. Coman, B. Dubois, A. Duggento, S. Durrleman, M.T. Ferretti, N. George, R. Genthon, M.O. Habert, K. Herholz, Y. Koronyo, M. Koronyo-Hamaoui, F. Lamari, T. Langevin, S. Lehéricy, J. Lorenceau, C. Neri, R. Nistico, F. Nyasse-Messene, C. Ritchie, S. Rossi, E. Santarnecchi, O. Sporns, S.R. Verdooner, A. Vergallo, N. Villain, E. Younesi, F. Garaci, S. Lista Revolution of Alzheimer Precision Neurology - Passageway of Systems Biology and Neurophysiology, Journal of Alzheimer's Disease, 2018, doi: 10.3233/JAD-179932
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, A. Routier, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, Double diffeomorphism: combining morphometry and structural connectivity analysis, IEEE Trans. Medical Imaging, 2018, to appear
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, A. Routier, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, Double diffeomorphism: combining morphometry and structural connectivity analysis, IEEE Trans. Medical Imaging, 11 (1), 802-833, 2018
  • B. Gris, S. Durrleman, A. Trouvé, A sub-Riemannian modular framework for diffeomorphism based analysis of shape ensembles, SIAM Journal on Imaging Sciences, to appear
  • A. Beaudet et al., The endocranial shape of Australopithecus africanus: surface analysis of the endocasts of Sts 5 and Sts 60, Journal of Anatomy, to appear
  • J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations, Journal of Machine Learning Research, 18(133):1−33, 2017
  • Anne Bertrand, Junhao Wen, Daisy Rinaldi, Marion Houot, Sabrina Sayah, Agnès Camuzat, Clémence Fournier, Sabrina Fontanella, Alexandre Routier, Philippe Couratier, Florence Pasquier, Marie-Odile Habert, Didier Hannequin, Olivier Martinaud, Paola Caroppo, Richard Levy, Bruno Dubois, Alexis Brice, Stanley Durrleman, Olivier Colliot, Isabelle Le Ber and PREVDEMALS Study Group, Early cognitive, structural and microstructural changes in c9orf72 presymptomatic carriers before 40 years of age, JAMA Neurology, 75 (2), 236-245, 2018
  • J. Fishbaugh, S. Durrleman, M. Prastawa, G. Gerig, Geodesic Shape Regression with Multiple Geometries and Sparse Parameters, Medical Image Analysis,pdf
  • Th. Jacquemont, F. De Vico Fallani, A. Bertrand, S. Epelbaum, A. Routier, B Dubois, H. Hampel, S. Durrleman, O. Colliot, Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment, Neurobiology of Aging, Vol 55, pp 177-189, 2017, doi:10.1016/j.neurobiolaging.2017.03.023
  • H. Hampel, S.E. O'Bryant, S. Durrleman, E. Younesi, K. Rojkova, V. Escott-Price, J.-C. Corvol, K. Broich, B. Dubois, S. Lista A Precision Medicine Initiative for Alzheimer's disease: the road ahead to biomarker-guided integrative disease modeling, Climacteric, Vol 20(2), 107-118doi
  • A. Beaudet, J. Dumoncel, F. de Beer, B. Duployer, S. Durrleman, E. Gilissen, J. Hoffman, C. Tenailleau, J. F. Thackeray, J. Braga, Morphoarchitectural variation in South African fossil cercopithecoid endocasts, Journal of Human Evolution, 101, 65-78 (2016), pdf
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, S. Lecomte, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, A Bayesian framework for joint morphometry of surface and curve meshes in multi-object complexes, Medical Image Analysis, Vol 35, p 458-474, 2017
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, S. Lecomte, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, Parsimonious Approximation of Streamline Trajectories in White Matter Fiber Bundles, IEEE Transactions on Medical Imaging (TMI), Vol 35 (12), pp 2609-2919, 2016
  • P. Caroppo, M.-O. Habert, S. Durrleman, A. Funkiewiez, V. Perlbarg, V. Hahn, H. Bertin, M. Gaubert, A. Rotuier, D. Hannequin, V. Deramecourt, F. Pasquier, S. Rivaud-Pechoux, M. Vercelletto, G. Edouart, R. Valabregue, P. Lejeune, M. Didic, J.-C. Corvol, H. Benali, S. Lehericy, B. Dubois, O. Colliot, A. Brice, I. Le Ber, the Predict-PGRN study group, Lateral temporal lobe: an early imaging marker of the presymptomatic GNR disease?, Journal of Alzheimer's Disease, 2015
  • S. Allassonnière, S. Durrleman, E. Kuhn, Bayesian Mixed Effect Atlas Estimation with a Diffeomorphic Deformation Model, SIAM J. Imaging Science, 2015 (accepted for publication)
  • E. Bron et al., Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge, Neuroimage, 2015 (in press).
  • S. Durrleman, M. Prastawa, N. Charon, J. R. Korenberg, S. Joshi, G. Gerig, A. Trouvé, Morphometry of anatomical shape complexes with dense deformations and sparse parameters, NeuroImage, 101(1):35-49, 2014, pdf, link
  • B. Ng, M. Toews, S. Durrleman and Y. Shi, Shape Analysis for Brain Structures: A Review, in Shape Analysis in Medical Image Analysis, S. Li and J.M Tavares (Eds.), Springer, 2014, link
  • I. Rekik, S. Allassonnière, S. Durrleman, T. Carpenter and J. M. Wardlaw, Spatio-temporal dynamic simulation of acute perfusion/diffusion ischemic stroke lesions evolution: a pilot study derived from longitudinal MR patient data, Computational and Mathematical Methods in Medicine, Vol 2013, Article ID 283593, 13 pages, 2013, pdf
  • S. Durrleman, X. Pennec, A. Trouvé, J. Braga, G. Gerig, N. Ayache, Toward a comprehensive framework for the spatiotemporal statistical analysis of longitudinal shape data, International Journal of Computer Vision, 2013, 103(1):22-59, doi, pdf
  • S. Durrleman, S. Allassonnière, S. Joshi, Sparse adaptive parameterization of variability in image ensembles, International Journal of Computer Vision, 2013, 101(1):161-183, doi pdf
  • S. Durrleman, X. Pennec, A. Trouvé, N. Ayache and J. Braga, Comparison of the endocranial ontogenies between chimpanzees and bonobos via temporal regression and spatiotemporal registration, Journal of Human Evolution, 62(1):74-88, 2012, doi pdf
  • T. Mansi, I. Voigt, B. Leonardi, X. Pennec, S. Durrleman, M. Sermesant, H. Delingette, A. M. Taylor, Y. Boudjemline, G. Pongiglione, and N. Ayache, A Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot, Trans. on Medical Imaging, 9(30):1605-1616, 2011, pdf
  • S. Durrleman, P. Fillard, X. Pennec, A. Trouvé, N. Ayache, Registration, Atlas Estimation and Variability Analysis of White Matter Fiber Bundles Modeled as Currents, NeuroImage 55(3):1073-1090, 2011, pdf
  • S. Durrleman, X. Pennec, A. Trouvé, N. Ayache, Statistical Models on Sets of Curves and Surfaces based on Currents, Medical Image Analysis, 13(5):793-808, October 2009, pdf
  • S. Durrleman, X. Pennec, A. Trouvé, P. Thompson, N. Ayache, Inferring Brain Variability from Diffeomorphic Deformations of Currents: an integrative approach, Medical Image Analysis, 12(5):626-637, September 2008, pdf
  • S. Durrleman, F. Boschetti, A. Ord, and K. Regenauer-Lieb, Automatic Detection of Particle Aggregations in Particles Simulation of Rock Deformation, Geochemistry, Geophysics, Geosystems, 7, Q05006 (2006) doi:10.1029/2005GC001063

Peer-reviewed Conference Articles

  • A. Bône, M. Louis, O. Colliot, S. Durrleman, Learning low-dimensional representations of shape data sets with diffeomorphic autoencoders, Proc. Information Processing in Medical Imaging (IPMI), Springer, Lecture Notes in Computer Science, 2019, link
  • M. Louis, R. Couronne, I. Koval, B. Charlier, S. Durrleman, Riemannian geometry learning for disease progression modelling, Proc. Information Processing in Medical Imaging (IPMI), Springer, Lecture Notes in Computer Science, 2019, link
  • R. Couronne, J.-C. Corvol, S. Lehericy, M. Vidailhet, S. Durrleman, Learning disease progression models with longitudinal data and missing values, Proc. International Symposium on Biomedical Imaging (ISBI), 2019, link
  • W. Wei, E. Poirion, B. Bodini, S. Durrleman, N. Ayache, B. Stankoff, O. Colliot, Learning Myelin Content in Multiple Sclerosis from Multimodal MRI Through Adversarial Training, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI), Springer, Lecture Notes in Computer Science, V, 514-522, 2018
  • A. Bône, M. Louis, B. Martin, S. Durrleman, Deformetrica 4: an open-source software for statistical shape analysis, Proc. ShapeMI, MICCAI Workshop, Springer, Lecture Notes in Computer Science, 2018, link
  • A. Bône, O. Colliot, S. Durrleman, Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms, In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018) pdf
  • M. Ansart, S. Epelbaum, G. Gagliardi, O. Colliot, D. Dormont, B. Dubois, H. Hampel, S. Durrleman, Prediction of amyloidosis from neuropsychological and MRI data for cost effective inclusion of pre-symptomatic subjects in clinical trials, In Proc. Machine Learning in Clinical Decision Support (ML-CDS), Springer, Lecture Notes in Computer Science, Vol 10553, pp 357-364 (2017) pdf
  • A. Bône, M. Louis, A. Routier, J. Samper, M. Bacci, B. Charlier, O. Colliot, S. Durrleman, Prediction of the progression of subcortical brain structures in Alzheimer’s disease from baseline, In Proc. Mathematical Foundations of Computational Anatomy (MFCA), Springer, Lecture Notes in Computer Science, Vol 10551, pp 101-113 (2017)
  • I. Koval, J.-B. Schiratti, A. Routier, M. Bacci, O. Colliot, S. Allassonnière, S. Durrleman, Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks, In Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI), Springer, Lecture Notes in Computer Science, Vol 10433, pp 451-459 (2017) pdf
  • M. Louis, A. Bône, B. Charlier, S. Durrleman, Parallel transport in shape analysis : a scalable numerical scheme for Riemannian manifolds, In Proc. Geometric Science of Information (GSI), Springer, Lecture Notes in Computer Science, Vol 10589, pp 29-37 (2017)
  • C. Cury, M. Lorenzi, D. Cash, J. M. Nicholas, A. Routier, J. Rohrer, S. Ourselin, S. Durrleman, M. Modat, Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease, In International Workshop on Spectral and Shape Analysis in Medical Imaging (SSAMI), Springer, LNCS 10126, p63-75, 2016, pdf
  • J. Dumoncel, G. Subsol, S. Durrleman, J.-P. Jessel, A. Beaudet, J. Braga, How to build an average model when samples are variably incomplete? Application to fossil data?, In Workshop on Biomedical Image Registration (WBIR), 2016, pdf
  • J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, Learning spatiotemporal trajectories from manifold-valued longitudinal data, In Neural Information Processing System (NIPS), 2015, pdf
  • B. Gris, S. Durrleman, A. Trouvé, A sub-Riemannian modular approach for diffeomorphic deformations, In Geometric Science of Information (GSI'15), 2015, Springer LNCS, Vol 9389, pp 39-47 pdf
  • J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data, 5th MICCAI Workshop on Mathematical Foundations of Computational Anatomy, 2015
  • J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, A Mixed­ Effect Model with Time Reparametrization for Longitudinal Univariate Manifold-valued Data, In Proc. Information Processing in Medical Imaging (IPMI), 2015, Springer LNCS Vol 9123, pp 564-575
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, S. Lecomte, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, Joint Morphometry of Fiber Tracts and Gray Matter structures using Double Diffeomorphisms, In Proc. Information Processing in Medical Imaging (IPMI), 2015, Springer LNCS, Vol 9123, pp 275-287
  • A. B. G. Fouquier, S. Durrleman, J. Yelnik, S. Fernandez-Vidal, E. Bardinet, Iconic-Geometric Nonlinear Registration of a Basal Ganglia Atlas for Deep Brain Stimulation Planning, In Proc. of MICCAI Workshop on Deep Brain Stimulation Methodological Challenges (DBSMC'14), 2014, pdf
  • A. Routier, P. Gori, A. B. Graciano Fouquier, S. Lecomte, O. Colliot, S. Durrleman, Evaluation of morphometric descriptors of deep brain structures for the automatic classification of patients with Alzheimer's disease, mild cognitive impairment and elderly controls, In MICCAI challenge on Computer-Aided Diagnosis of Dementia based on structural MRI data (CADDementia), 2014, pdf
  • P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, F. de Vico Fallani, M. Chavez, S. Lecomte, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, A Prototype Representation to Approximate White Matter Bundles with Weighted Currents, In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI'14), Part III LNCS 8675, pp 289-296, 2014, pdf
  • P. Muralidharan, J. Fishbaugh, H. J. Johnson, S. Durrleman, J. S. Paulsen, G. Gerig, P. T. Fletcher, Diffeomorphic Shape Trajectories for Improved Longitudinal Segmentation and Statistics, In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI'14), Part III LNCS 8675, pp 49-56, 2014, pdf
  • J. Fishbaugh, M. Prastawa, G. Gerig, S. Durrleman, Geodesic image regression of image and shape data for improved modeling of 4D trajectories, In Proceedings of IEEE 11th International Symposium on Biomedical Imaging (ISBI), pp 385-388 2014,
  • P. Gori, O. Colliot, Y. Worbe, L. Marrakchi-Kacem, S. Lecomte, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman, Bayesian Atlas Estimation for the Variability Analysis of Shape Complexes, In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI'13), LNCS 8149, pp 267-274, 2013
  • J. Fishbaugh, M. Prastawa, G. Gerig, S. Durrleman, Geodesic image regression with a sparse parameterization of diffeomorphisms, In Proceedings of Geometric Science of Information (GSI), LNCS 8085, pp 95-102, 2013,
  • J. Fishbaugh, M. Prastawa, G. Gerig, S. Durrleman, Geodesic Shape Regression in the Framework of Currents, In Proceedings of Information Processing in Medical Imaging (IPMI'13), LNCS 7917, pp 718-729, 2013, pdf
  • A. Imperiale, A. Routier, S. Durrleman, P. Moireau, Improving Efficiency of Data Assimilation Procedure for a Biomechanical Heart Model by Representing Surfaces as Currents, In Proceedings of Functional Imaging and Modeling of the Heart (FIMH'13), LNCS 7945, pp 342-351, 2013,
  • S. Durrleman, M. Prastawa, J.R. Korenberg, S. Joshi, A. Trouvé, G. Gerig, Topology Preserving Atlas Construction from Shape Data without Correspondence using Sparse Parameters, In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI'12), LNCS 7512, pp 223-230, 2012 pdf and supplementary material
  • J. Fishbaugh, M. Prastawa, S. Durrleman, J. P. Piven, G. Gerig, Analysis of Longitudinal Shape Variability via Subject Specific Growth Modeling, In Proceedings of Medical Image Computing and Computer Aided Intervention (MICCAI'12), LNCS 7510, pp 731-738, 2012
  • A. Sharma, S. Durrleman, J.H. Gilmore, G. Gerig, Longitudinal Growth Modeling of Discrete-Time Functions with Application to DTI Tract Evolution in Early Neurodevelopment, In Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), pp 1397-1400, 2012
  • J. Fishbaugh, S. Durrleman, J. Piven, G. Gerig, A framework for longitudinal data analysis via shape regression, Proc. of SPIE Medical Imaging, Image Processing, Vol. 8314, 2012, doi
  • J. Fishbaugh, S. Durrleman, G. Gerig, Estimation of Smooth Growth Trajectories with Controlled Acceleration from Time Series Shape Data, Proc. of Medical Image Computing and Computer Assisted Intervention (MICCAI'11), LNCS 6892, pp. 401-408 September 2011, pdf
  • S. Durrleman, M. Prastawa, G. Gerig, S. Joshi, Optimal data-driven sparse parameterization of diffeomorphisms for population analysis, Proc. of Information Processing in Medical Imaging (IPMI'11), LNCS 6801, pp 123-134 July 2011, pdf
  • S. Durrleman, X. Pennec, A. Trouvé, N. Ayache and J. Braga, Comparison of the endocast growth of chimpanzees and bonobos via temporal regression and spatiotemporal registration, 1st workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data, Beijing, Septembre 2010, pdf
  • S. Durrleman, P. Fillard, X. Pennec, A. Trouvé and N. Ayache, A Statistical Model of White Matter Fiber Bundles based on Currents, Proc. of Information Processing in Medical Imaging (IPMI'09), LNCS 5636, pp 114-125 July 2009, pdf
  • S. Durrleman, X. Pennec, A. Trouvé, G. Gerig and N. Ayache, Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI'09), LNCS 5761, pp 297-304 September 2009, pdf
  • V. Gorbunova, S. Durrleman, P. Lo, X. Pennec, M. de Bruijne Lung CT-Registration Combining Intensities, Curves and Surfaces, Proc. IEEE International Symposium on Biomedical Imaging (ISBI'10), September 2009, pdf
  • V. Gorbunova, S. Durrleman, P. Lo, X. Pennec, M. de Bruijne Curve- and surface-based registration of lung CT images via currents, Proc. of the second International Workshop on Pulmonary Image Analysis, September 2009, pdf
  • T. Mansi, S. Durrleman, B. Bernhardt, M. Sermesant, H. Delingette, I. Voigt, Ph. Lurz, A. M. Taylor, J. Blanc, Y. Boudjemline, X. Pennec and N. Ayache, A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI'09), LNCS 5761, pp 214-221 September 2009, pdf
  • S. Durrleman, X. Pennec, A. Trouvé and N. Ayache, Sparse Approximations of Currents for Statistics on Curves and Surfaces, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS 5242, pp 390-398 September 2008, pdf
  • S. Durrleman, X. Pennec, A. Trouvé and N. Ayache, A Forward Model to Build Unbiased Atlases from Curves and Surfaces, Proc. of the International Workshop on the Mathematical Foundations of Computational Anatomy (MFCA-2008), September 2008, pdf
  • S. Durrleman, X. Pennec, A. Trouvé and N. Ayache, Measuring Brain Variability via Sulcal Lines Registration: a Diffeomorphic Approach, Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS 4791, pp 675-682 October 2007, pdf