EN FR
EN FR


previous Previous | up Home


Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1P. Moceri.

    From normal right ventricle to pathology : shape and function analysis with different loading conditions using imaging and modelling, Université Côte d'Azur, January 2018.

    https://tel.archives-ouvertes.fr/tel-01781331

Articles in International Peer-Reviewed Journals

  • 2O. Bernard, A. Lalande, C. Zotti, F. Cervenansky, X. Yang, P.-A. Heng, I. Cetin, K. Lekadir, O. Camara, M. A. G. Ballester, G. Sanroma, S. Napel, S. Petersen, G. Tziritas, E. Grinias, M. Khened, V. A. Kollerathu, G. Krishnamurthi, M.-M. Rohé, X. Pennec, M. Sermesant, F. Isensee, P. Jager, K. H. Maier-Hein, P. M. Full, I. Wolf, S. Engelhardt, C. Baumgartner, L. Koch, J. Wolterink, I. Isgum, Y. Jang, Y. Hong, J. Patravali, S. Jain, O. Humbert, P.-M. Jodoin.

    Deep Learning Techniques for Automatic MRI Cardiac Multi-structures Segmentation and Diagnosis: Is the Problem Solved?, in: IEEE Transactions on Medical Imaging, May 2018, vol. 37, no 11, pp. 2514-2525. [ DOI : 10.1109/TMI.2018.2837502 ]

    https://hal.archives-ouvertes.fr/hal-01803621
  • 3R. Cabrera Lozoya, B. Berte, H. Cochet, P. Jaïs, N. Ayache, M. Sermesant.

    Model-based Feature Augmentation for Cardiac Ablation Target Learning from Images, in: IEEE Transactions on Biomedical Engineering, March 2018, 1 p. [ DOI : 10.1109/TBME.2018.2818300 ]

    https://hal.inria.fr/hal-01744142
  • 4N. Cedilnik, J. Duchateau, R. Dubois, F. Sacher, P. Jaïs, H. Cochet, M. Sermesant.

    Fast Personalized Electrophysiological Models from CT Images for Ventricular Tachycardia Ablation Planning, in: EP-Europace, November 2018, vol. 20.

    https://hal.inria.fr/hal-01875533
  • 5M. Corneli, C. Bouveyron, P. Latouche, F. Rossi.

    The dynamic stochastic topic block model for dynamic networks with textual edges, in: Statistics and Computing, 2018. [ DOI : 10.1007/s11222-018-9832-4 ]

    https://hal.archives-ouvertes.fr/hal-01621757
  • 6C. Cury, S. Durrleman, D. Cash, M. Lorenzi, J. M. Nicholas, M. Bocchetta, J. C. Van Swieten, B. Borroni, D. Galimberti, M. Masellis, M. C. Tartaglia, J. Rowe, C. Graff, F. Tagliavini, G. B. Frisoni, R. Laforce, E. Finger, A. de Mendonça, S. Sorbi, S. Ourselin, J. Rohrer, M. Modat, C. Andersson, S. Archetti, A. Arighi, L. Benussi, S. Black, M. Cosseddu, M. Fallstrm, C. G. Ferreira, C. Fenoglio, N. Fox, M. Freedman, G. Fumagalli, S. Gazzina, R. Ghidoni, M. Grisoli, V. Jelic, L. Jiskoot, R. Keren, G. Lombardi, C. Maruta, L. Meeter, R. van Minkelen, B. Nacmias, L. Ijerstedt, A. Padovani, J. Panman, M. Pievani, C. Polito, E. Premi, S. Prioni, R. Rademakers, V. Redaelli, E. Rogaeva, G. Rossi, M. Rossor, E. Scarpini, D. Tang-Wai, H. Thonberg, P. Tiraboschi, A. Verdelho, J. Warren.

    Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort, in: NeuroImage, March 2019, vol. 188, pp. 282-290. [ DOI : 10.1016/j.neuroimage.2018.11.063 ]

    https://www.hal.inserm.fr/inserm-01958916
  • 7N. Duchateau, M. Sermesant, H. Delingette, N. Ayache.

    Model-based generation of large databases of cardiac images: synthesis of pathological cine MR sequences from real healthy cases, in: IEEE Transactions on Medical Imaging, 2018, vol. 37, pp. 755-766. [ DOI : 10.1109/TMI.2017.2714343 ]

    https://hal.inria.fr/hal-01533788
  • 8L. Feng, P. Alliez, L. Busé, H. Delingette, M. Desbrun.

    Curved Optimal Delaunay Triangulation, in: ACM Transactions on Graphics, August 2018, vol. 37, no 4, 16 p. [ DOI : 10.1145/3197517.3201358 ]

    https://hal.inria.fr/hal-01826055
  • 9S. Ferraris, J. Van Der Merwe, L. van Der Veeken, F. Prados, J. E. Iglesias, M. Lorenzi, A. Melbourne, M. M. Modat, W. Gsell, J. Deprest, T. Vercauteren.

    A magnetic resonance multi-atlas for the neonatal rabbit brain, in: NeuroImage, October 2018, vol. 179, pp. 187 - 198. [ DOI : 10.1016/j.neuroimage.2018.06.029 ]

    https://hal.inria.fr/hal-01843151
  • 10S. Giffard-Roisin, H. Delingette, T. Jackson, J. Webb, L. Fovargue, J. Lee, C. A. Rinaldi, R. Razavi, N. Ayache, M. Sermesant.

    Transfer Learning from Simulations on a Reference Anatomy for ECGI in Personalised Cardiac Resynchronization Therapy, in: TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2018, vol. 20. [ DOI : 10.1109/TBME.2018.2839713 ]

    https://hal.archives-ouvertes.fr/hal-01796483
  • 11P. Gori, O. Colliot, L. M. Kacem, Y. Worbe, A. Routier, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman.

    Double diffeomorphism: combining morphometry and structural connectivity analysis, in: IEEE Transactions on Medical Imaging, September 2018, vol. 37, no 9, pp. 2033-2043. [ DOI : 10.1109/TMI.2018.2813062 ]

    https://hal.archives-ouvertes.fr/hal-01709847
  • 12R. Karim, L.-E. Blake, J. Inoue, Q. Tao, S. Jia, R. J. J. Housden, P. Bhagirath, J.-L. Duval, M. Varela, J. Behar, L. Cadour, R. J. van der Geest, H. Cochet, M. Drangova, M. Sermesant, R. Razavi, O. Aslanidi, R. Rajani, K. S. Rhode.

    Algorithms for left atrial wall segmentation and thickness – Evaluation on an open-source CT and MRI image database, in: Medical Image Analysis, December 2018, vol. 50, pp. 36 - 53. [ DOI : 10.1016/j.media.2018.08.004 ]

    https://hal.inria.fr/hal-01926935
  • 13M. Lorenzi, A. Altmann, B. Gutman, S. Wray, C. Arber, D. D. Hibar, N. J. Jahanshad, J. Schott, D. Alexander, P. M. Thompson, S. Ourselin.

    Susceptibility of brain atrophy to TRIB3 in Alzheimer’s disease, evidence from functional prioritization in imaging genetics, in: Proceedings of the National Academy of Sciences of the United States of America , 2018, vol. 115, no 12, pp. 3162-3167. [ DOI : 10.1073/pnas.1706100115 ]

    https://hal.archives-ouvertes.fr/hal-01756811
  • 14K. Mcleod, K. Tøndel, L. Calvet, M. Sermesant, X. Pennec.

    Cardiac Motion Evolution Model for Analysis of Functional Changes Using Tensor Decomposition and Cross-Sectional Data, in: IEEE Transactions on Biomedical Engineering, March 2018, vol. 65, no 12, pp. 2769 - 2780. [ DOI : 10.1109/TBME.2018.2816519 ]

    https://hal.inria.fr/hal-01736454
  • 15N. Miolane, S. Holmes, X. Pennec.

    Topologically constrained template estimation via Morse-Smale complexes controls its statistical consistency, in: SIAM Journal on Applied Algebra and Geometry, 2018, vol. 2, no 2, pp. 348-375. [ DOI : 10.1137/17M1129222 ]

    https://hal.inria.fr/hal-01655366
  • 16P. Moceri, N. Duchateau, D. Baudouy, E.-D. Schouver, S. Leroy, F. Squara, E. Ferrari, M. Sermesant.

    Three-dimensional right-ventricular regional deformation and survival in pulmonary hypertension, in: European Heart Journal - Cardiovascular Imaging, 2018, vol. 19, pp. 450-458. [ DOI : 10.1093/ehjci/jex163 ]

    https://hal.inria.fr/hal-01533793
  • 17P. Moceri, M. Sermesant, D. Baudouy, E. Ferrari, N. Duchateau.

    Right Ventricular Function Evolution With Pregnancy in Repaired Tetralogy of Fallot, in: Canadian Journal of Cardiology, October 2018, vol. 34, no 10, pp. 1369.e9 - 1369.e11. [ DOI : 10.1016/j.cjca.2018.06.010 ]

    https://hal.inria.fr/hal-01926967
  • 18R. Molléro, X. Pennec, H. Delingette, N. Ayache, M. Sermesant.

    Population-based priors in cardiac model personalisation for consistent parameter estimation in heterogeneous databases, in: International Journal for Numerical Methods in Biomedical Engineering, September 2018. [ DOI : 10.1002/cnm.3158 ]

    https://hal.inria.fr/hal-01922719
  • 19C. Nioche, F. Orlhac, S. Boughdad, S. Reuzé, J. Goya-Outi, C. Robert, C. Pellot-Barakat, M. Soussan, F. Frouin, I. Buvat.

    LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity, in: Cancer Research, August 2018, vol. 78, no 16, pp. 4786 - 4789. [ DOI : 10.1158/0008-5472.CAN-18-0125 ]

    https://hal.archives-ouvertes.fr/hal-01938545
  • 20F. Orlhac, F. Frouin, C. Nioche, N. Ayache, I. Buvat.

    Validation of a method to compensate multicenter effects affecting CT radiomic features, in: Radiology, 2018.

    https://hal.archives-ouvertes.fr/hal-01953538
  • 21F. Orlhac, P.-A. Mattei, C. Bouveyron, N. Ayache.

    Class-specific Variable Selection in High-Dimensional Discriminant Analysis through Bayesian Sparsity, in: Journal of Chemometrics, November 2018, e3097 p. [ DOI : 10.1002/cem.3097 ]

    https://hal.archives-ouvertes.fr/hal-01811514
  • 22X. Pennec.

    Barycentric Subspace Analysis on Manifolds, in: Annals of Statistics, July 2018, vol. 46, no 6A, pp. 2711-2746, https://arxiv.org/abs/1607.02833v2. [ DOI : 10.1214/17-AOS1636 ]

    https://hal.archives-ouvertes.fr/hal-01343881
  • 23M.-M. Rohé, M. Sermesant, X. Pennec.

    Low-Dimensional Representation of Cardiac Motion Using Barycentric Subspaces: a New Group-Wise Paradigm for Estimation, Analysis, and Reconstruction, in: Medical Image Analysis, April 2018, vol. 45, pp. 1-12. [ DOI : 10.1016/j.media.2017.12.008 ]

    https://hal.inria.fr/hal-01677685
  • 24M. A. Scelzi, R. R. Khan, M. Lorenzi, C. Leigh, M. D. Greicius, J. M. Schott, S. Ourselin, A. Altmann.

    Genetic study of multimodal imaging Alzheimer’s disease progression score implicates novel loci, in: Brain - A Journal of Neurology , July 2018, vol. 141, no 7, pp. 2167 - 2180. [ DOI : 10.1093/brain/awy141 ]

    https://hal.inria.fr/hal-01843380
  • 25A. A. Suinesiaputra, P. A. Ablin, X. A. Albà, M. Alessandrini, J. A. Allen, W. Bai, S. Çimen, P. Claes, B. R. Cowan, J. D'Hooge, N. Duchateau, J. Ehrhardt, A. F. Frangi, A. A. Gooya, V. Grau, K. Lekadir, A. A. Lu, A. A. Mukhopadhyay, I. Oksuz, N. Parajuli, X. Pennec, M. Pereañez, C. Pinto, P. Piras, M.-M. Rohé, D. R. Rueckert, D. Säring, M. Sermesant, K. Siddiqi, M. Tabassian, L. Teresi, S. A. Tsaftaris, M. Wilms, A. A. Young, X. Zhang, P. Medrano-Gracia.

    Statistical shape modeling of the left ventricle: myocardial infarct classification challenge, in: IEEE Journal of Biomedical and Health Informatics, March 2018, vol. 22, no 3, pp. 503-515. [ DOI : 10.1109/JBHI.2017.2652449 ]

    https://hal.inria.fr/hal-01533805
  • 26Q. Zheng, H. Delingette, N. Duchateau, N. Ayache.

    3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation, in: IEEE Transactions on Medical Imaging, April 2018.

    https://hal.inria.fr/hal-01753086
  • 27Y. Zhou, S. Giffard-Roisin, M. De Craene, S. Camarasu-Pop, J. D'Hooge, M. Alessandrini, D. Friboulet, M. Sermesant, O. Bernard.

    A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences from the same Virtual Patients, in: IEEE Transactions on Medical Imaging, 2018, vol. 37, no 3, pp. 741-754. [ DOI : 10.1109/TMI.2017.2708159 ]

    https://hal.inria.fr/hal-01533366

International Conferences with Proceedings

  • 28S. Jia, A. Despinasse, Z. Wang, H. Delingette, X. Pennec, P. Jaïs, H. Cochet, M. Sermesant.

    Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss, in: Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01860285
  • 29S. Jia, N. Duchateau, P. Moceri, M. Sermesant, X. Pennec.

    Parallel Transport of Surface Deformations from Pole Ladder to Symmetrical Extension, in: ShapeMI MICCAI 2018: Workshop on Shape in Medical Imaging, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01860274
  • 30J. Krebs, T. Mansi, B. Mailhé, N. Ayache, H. Delingette.

    Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration, in: Deep Learning in Medical Image Analysis (MICCAI workshop), Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01845688
  • 31M. Lorenzi, M. Filippone.

    Constraining the Dynamics of Deep Probabilistic Models, in: ICML 2018 - The 35th International Conference on Machine Learning, Stockholm, Sweden, PMLR - Proceedings of Machine Learning Research, July 2018, vol. 80, pp. 3233-3242, https://arxiv.org/abs/1802.05680 - 13 pages.

    https://hal.inria.fr/hal-01843006
  • 32F. Orlhac, C. Bouveyron, T. Pourcher, L. Jing, J.-M. Guigonis, J. Darcourt, N. Ayache, O. Humbert.

    Identification des cancers mammaires triple-négatifs : analyse statistique de variables radiomiques issues des images TEP et de variables métabolomiques, in: 2018 - 4èmes Journées Francophones de Médecine Nucléaire, Lille, France, Médecine Nucléaire, May 2018, vol. 42, no 3, 169 p.

    https://hal.archives-ouvertes.fr/hal-01736154
  • 33F. Orlhac, O. Humbert, T. Pourcher, L. Jing, J.-M. Guigonis, J. Darcourt, N. Ayache, C. Bouveyron.

    Analyse statistique de données radiomiques et métabolomiques : prédiction des lésions mammaires triple-négatives, in: 12ème Conférence Francophone d’Epidémiologie Clinique (EPICLIN) et 25èmes Journées des statisticiens des Centre de Lutte Contre le Cancer (CLCC), Nice, France, Revue d'épidémiologie et de santé publique, May 2018, vol. 66, no s3, pp. S180-S181. [ DOI : 10.1016/j.respe.2018.03.307 ]

    https://hal.archives-ouvertes.fr/hal-01736164
  • 34F. Orlhac, O. Humbert, T. Pourcher, L. Jing, J.-M. Guigonis, J. Darcourt, N. Ayache, C. Bouveyron.

    Statistical analysis of PET radiomic features and metabolomic data: prediction of triple-negative breast cancer, in: SNMMI Annual Meeting, Philadelphia, United States, Journal of Nuclear Medicine, June 2018, vol. 59, no supplement 1, 1755 p.

    https://hal.archives-ouvertes.fr/hal-01759330
  • 35S. R. Santiago Smith, B. A. Gutman, E. Romero, P. M. Thompson, A. Altmann, M. Lorenzi.

    Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data, in: International Symposium on Biomedical Imaging, Venice, Italy, April 2018.

    https://hal.inria.fr/hal-01963637
  • 36W. 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, in: MICCAI 2018 – 21st International Conference On Medical Image Computing & Computer Assisted Intervention, Granada, Spain, September 2018, vol. 11072. [ DOI : 10.1007/978-3-030-00931-1_59 ]

    https://hal.inria.fr/hal-01810822

Conferences without Proceedings

  • 37L. Antelmi, N. Ayache, P. Robert, M. Lorenzi.

    Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease, in: Understanding and Interpreting Machine Learning in Medical Image Computing Applications, Granada, Spain, September 2018.

    https://hal.archives-ouvertes.fr/hal-01882463
  • 38C. A. Nader, N. Ayache, P. Robert, M. Lorenzi.

    Alzheimer's Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes, in: Machine Learning in Clinical Neuroimaging (MLCN) workshop, Granada, Spain, September 2018, https://arxiv.org/abs/1808.06367.

    https://hal.archives-ouvertes.fr/hal-01882450
  • 39F. Orlhac, O. Humbert, S. Boughdad, M. Lasserre, M. Soussan, C. Nioche, N. Ayache, J. Darcourt, F. Frouin, I. Buvat.

    Validation d'une méthode d'harmonisation des mesures SUV et des variables radiomiques pour les études TEP multicentriques rétrospectives, in: 2018 - 4èmes Journées Francophones de Médecine Nucléaire, Lille, France, May 2018, vol. 42, no 3, 170 p.

    https://hal.archives-ouvertes.fr/hal-01736147
  • 40F. Orlhac, O. Humbert, S. Boughdad, M. Lasserre, M. Soussan, C. Nioche, N. Ayache, J. Darcourt, F. Frouin, I. Buvat.

    Validation of a harmonization method to correct for SUV and radiomic features variability in multi-center studies, in: SNMMI Annual Meeting, Philadelphia, United States, June 2018, vol. 59, 288 p.

    https://hal.archives-ouvertes.fr/hal-01759334
  • 41A. Schmutz, J. Jacques, C. Bouveyron, L. Cheze, P. Martin.

    Données fonctionnelles multivariées issues d'objets connectés : une méthode pour classer les individus, in: Journées des Statistiques, Saclay, France, May 2018.

    https://hal.inria.fr/hal-01784279
  • 42W. Wei, E. Poirion, B. Bodini, S. Durrleman, O. Colliot, B. Stankoff, N. Ayache.

    FLAIR MR Image Synthesis By Using 3D Fully Convolutional Networks for Multiple Sclerosis, in: ISMRM-ESMRMB 2018 - Joint Annual Meeting, Paris, France, June 2018, pp. 1-6.

    https://hal.inria.fr/hal-01723070

Scientific Books (or Scientific Book chapters)

  • 43N. Ayache.

    L'imagerie médicale à l'heure de l'intelligence artificielle, in: Santé et intelligence artificielle, C. Villani, B. Nordlinge (editors), CNRS Editions, October 2018, pp. 151-154.

    https://hal.inria.fr/hal-01882558
  • 44C. Bouveyron.

    Apprentissage statistique en grande dimension et application au diagnostic oncologique par radiomique, in: Santé et intelligence artificielle, C. Villani, e. Nordlinge (editors), CNRS Editions, October 2018, pp. 179-189.

    https://hal.archives-ouvertes.fr/hal-01884468

Books or Proceedings Editing

  • 45M. Bauer, N. Charon, P. Harms, B. Khesin, A. L. Brigant, E. Maignant, S. Marsland, P. Michor, X. Pennec, S. C. Preston, S. Sommer, F.-X. Vialard (editors)

    Math in the Black Forest: Workshop on New Directions in Shape Analysis, Published by the authors, November 2018, https://arxiv.org/abs/1811.01370 - 27 pages, 4 figures.

    https://hal.inria.fr/hal-01923588

Internal Reports

  • 46S. Silva, B. Gutman, E. Romero, P. M. Thompson, A. Altmann, M. Lorenzi, U. K. Adni.

    Federated learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data (Supplementary Material), Inria & Université Cote d'Azur, CNRS, I3S, Sophia Antipolis, France, October 2018.

    https://hal.inria.fr/hal-01895800

Other Publications

  • 47C. Abi Nader, N. Ayache, V. Manera, P. Robert, M. Lorenzi.

    Disentangling spatio-temporal patterns of brain changes in large-scale brain imaging databases through Independent Gaussian Process Analysis, May 2018, vol. Revue d'Épidémiologie et de Santé Publique, no 66, S159 p, 12ème Conférence Francophone d'Epidémiologie Clinique (EPICLIN) et 25èmes Journées des statisticiens des Centre de Lutte Contre le Cancer (CLCC), Poster. [ DOI : 10.1016/j.respe.2018.03.108 ]

    https://hal.archives-ouvertes.fr/hal-01826517
  • 48L. Antelmi, N. Ayache, P. Robert, M. Lorenzi.

    Supplementary Material of the paper: "Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease", July 2018, Supplementary Material of the paper: "Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease". Paper accepted at the 1st International Workshop on Machine Learning in Clinical Neuroimaging, in conjunction with MICCAI 2018, September 20, Granada (Spain).

    https://hal.inria.fr/hal-01844733
  • 49L. Antelmi, M. Lorenzi, V. Manera, P. Robert, N. Ayache.

    A method for statistical learning in large databases of heterogeneous imaging, cognitive and behavioral data, 12e Conférence francophone d’Épidémiologie clinique 25e Journée des statisticiens des Centres de lutte contre le cancer, Elsevier, May 2018, vol. 66, no 3, S180 p, EPICLIN 2018 - 12ème Conférence Francophone d’Epidémiologie Clinique / CLCC 2018 - 25èmes Journées des statisticiens des Centre de Lutte Contre le Cancer, Poster. [ DOI : 10.1016/j.respe.2018.03.306 ]

    https://hal.inria.fr/hal-01827389
  • 50L. Bergé, C. Bouveyron, M. Corneli, P. Latouche.

    The Latent Topic Block Model for the Co-Clustering of Textual Interaction Data, July 2018, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01835074
  • 51M. Corneli, C. Bouveyron, P. Latouche.

    Co-Clustering of ordinal data via latent continuous random variables and a classification EM algorithm, January 2019, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01978174
  • 52C. Cury, S. Durrleman, D. M. Cash, M. Lorenzi, J. M. Nicholas, M. Bocchetta, J. C. Van Swieten, B. Borroni, D. Galimberti, M. Masellis, M. C. Tartaglia, J. Rowe, C. Graff, F. Tagliavini, G. B. Frisoni, R. J. Laforce, E. Finger, A. de Mendonça, S. Sorbi, S. Ourselin, J. D. Rohrer, M. M. Modat.

    Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: applied to GENFI study, August 2018, working paper or preprint. [ DOI : 10.1101/385427 ]

    https://hal.inria.fr/hal-01856906
  • 53J. Krebs, H. Delingette, B. Mailhé, N. Ayache, T. Mansi.

    Learning a Probabilistic Model for Diffeomorphic Registration, January 2019, https://arxiv.org/abs/1812.07460 - Under review.

    https://hal.archives-ouvertes.fr/hal-01978339
  • 54N. Miolane, J. Mathe, C. Donnat, M. Jorda, X. Pennec.

    geomstats: a Python Package for Riemannian Geometry in Machine Learning, January 2019, https://arxiv.org/abs/1805.08308 - Preprint NIPS2018.

    https://hal.inria.fr/hal-01974572
  • 55P. Mlynarski, H. Delingette, A. Criminisi, N. Ayache.

    Deep Learning with Mixed Supervision for Brain Tumor Segmentation, December 2018, https://arxiv.org/abs/1812.04571 - Submitted to SPIE Journal of Medical Imaging.

    https://hal.inria.fr/hal-01952458
  • 56P. Mlynarski, H. Delingette, A. Criminisi, N. Ayache.

    3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context, September 2018, working paper or preprint.

    https://hal.inria.fr/hal-01883716
  • 57C. A. Nader, N. Ayache, P. Robert, M. Lorenzi.

    Appendix Alzheimer's Disease Modelling and Staging through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes, July 2018, Appendix.

    https://hal.archives-ouvertes.fr/hal-01849180
  • 58X. Pennec.

    Parallel Transport with Pole Ladder: a Third Order Scheme in Affine Connection Spaces which is Exact in Affine Symmetric Spaces, May 2018, https://arxiv.org/abs/1805.11436 - working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01799888
  • 59A. Saint-Dizier, J. Delon, C. Bouveyron.

    A unified view on patch aggregation, August 2018, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01865340
  • 60R. Sivera, H. Delingette, M. Lorenzi, X. Pennec, N. Ayache.

    A model of brain morphological changes related to aging and Alzheimer’s disease from cross-sectional assessments, December 2018, working paper or preprint.

    https://hal.inria.fr/hal-01948174
  • 61Q. Zheng, H. Delingette, N. Ayache.

    Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow, November 2018, working paper or preprint.

    https://hal.inria.fr/hal-01975880
  • 62Q. Zheng, H. Delingette, N. Duchateau, N. Ayache.

    3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation, March 2018, working paper or preprint.

    https://hal.inria.fr/hal-01755317


previous Previous | up Home