Bibliography

Major publications by the team in recent years

• 1S. Giffard-Roisin, T. Jackson, L. Fovargue, J. Lee, H. Delingette, R. Razavi, N. Ayache, M. Sermesant.
  Non-Invasive Personalisation of a Cardiac Electrophysiology Model from Body Surface Potential Mapping, in: IEEE Transactions on Biomedical Engineering, September 2017, vol. 64, n^o 9, pp. 2206 - 2218. [ DOI : 10.1109/TBME.2016.2629849 ]
• 2B. Khanal, N. Ayache, X. Pennec.
  Simulating Longitudinal Brain MRIs with known Volume Changes and Realistic Variations in Image Intensity, in: Frontiers in Neuroscience, February 2017, vol. 11, n^o Article 132, 18 p. [ DOI : 10.3389/fnins.2017.00132 ]
• 3L. Le Folgoc, H. Delingette, A. Criminisi, N. Ayache.
  Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements, in: Medical Image Analysis, February 2017, vol. 36, pp. 79 - 97. [ DOI : 10.1016/j.media.2016.09.008 ]
• 4M. Lorenzi, X. Pennec.
  Geodesics, Parallel Transport & One-parameter Subgroups for Diffeomorphic Image Registration, in: International Journal of Computer Vision, November 2013, vol. 105, n^o 2, pp. 111-127. [ DOI : 10.1007/s11263-012-0598-4 ]
• 5M. Lê, H. Delingette, J. Kalpathy-Cramer, E. R. Gerstner, T. Batchelor, J. Unkelbach, N. Ayache.
  MRI Based Bayesian Personalization of a Tumor Growth Model, in: IEEE Transactions on Medical Imaging, April 2016, vol. 35, n^o 10, pp. 2329-2339. [ DOI : 10.1109/TMI.2016.2561098 ]

Publications of the year

Doctoral Dissertations and Habilitation Theses

• 6T. Demarcy.
  Segmentation and study of anatomical variability of the cochlea from medical images, Université Côte d'Azur, July 2017.
  https://tel.archives-ouvertes.fr/tel-01609910
• 7L. Devilliers.
  Consistency of statistics in infinite dimensional quotient spaces, Université Côte d’Azur, November 2017.
  https://hal.inria.fr/tel-01683607
• 8S. Giffard-Roisin.
  Non-invasive Personalisation of Cardiac Electrophysiological Models from Surface Electrograms, Université côte d'azur, December 2017.
  https://hal.inria.fr/tel-01658489
• 9R. Molléro.
  Robust Personalisation of 3D Electromechanical Cardiac Models. Application to Heterogeneous and Longitudinal Clinical Databases, Université Nice Côte d'Azur, December 2017.
  https://hal.inria.fr/tel-01656290
• 10M.-M. Rohé.
  Reduced representation of segmentation and tracking in cardiac images for group-wise longitudinal analysis, Université Côte d'Azur, July 2017.
  https://hal.inria.fr/tel-01575292

Articles in International Peer-Reviewed Journals

• 11J. L. Bruse, A. Khushnood, K. Mcleod, G. Biglino, M. Sermesant, X. Pennec, A. M. Taylor, T.-Y. Hsia, S. Schievano.
  How successful is successful? Aortic arch shape after successful aortic coarctation repair correlates with left ventricular function, in: Journal of Thoracic and Cardiovascular Surgery, February 2017, vol. 153, n^o 2, pp. 418 - 427. [ DOI : 10.1016/j.jtcvs.2016.09.018 ]
  https://hal.inria.fr/hal-01387297
• 12J. L. Bruse, M. A. Zuluaga, A. Khushnood, K. Mcleod, H. N. Ntsinjana, T.-Y. Hsia, M. Sermesant, X. Pennec, A. M. Taylor, S. Schievano.
  Detecting clinically meaningful shape clusters in medical image data: metrics analysis for hierarchical clustering applied to healthy and pathological aortic arches, in: IEEE Transactions on Biomedical Engineering, February 2017, pp. 1 - 13. [ DOI : 10.1109/TBME.2017.2655364 ]
  https://hal.inria.fr/hal-01421202
• 13T. Demarcy, C. Vandersteen, N. Guevara, C. Raffaelli, D. Gnansia, N. Ayache, H. Delingette.
  Automated analysis of human cochlea shape variability from segmented μCT images, in: Computerized Medical Imaging and Graphics, 2017, vol. 59, n^o July 2017, pp. 1 - 12. [ DOI : 10.1016/j.compmedimag.2017.04.002 ]
  https://hal.inria.fr/hal-01528489
• 14L. Devilliers, S. Allassonnière, A. Trouvé, X. Pennec.
  Inconsistency of template estimation by minimizing of the variance/pre-variance in the quotient space, in: Entropy, June 2017, vol. 19, n^o 6, 28 p, https://arxiv.org/abs/1706.10125. [ DOI : 10.3390/e19060288 ]
  https://hal.inria.fr/hal-01543616
• 15L. Devilliers, S. Allassonnière, A. Trouvé, X. Pennec.
  Template estimation in computational anatomy: Fréchet means in top and quotient spaces are not consistent, in: SIAM Journal on Imaging Sciences, August 2017, vol. 10, n^o 3, pp. 1139-1169, https://arxiv.org/abs/1608.03703. [ DOI : 10.1137/16M1083931 ]
  https://hal.archives-ouvertes.fr/hal-01352707
• 16N. 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, 2017, In press. [ DOI : 10.1109/TMI.2017.2714343 ]
  https://hal.inria.fr/hal-01533788
• 17S. Giffard-Roisin, T. Jackson, L. Fovargue, J. Lee, H. Delingette, R. Razavi, N. Ayache, M. Sermesant.
  Non-Invasive Personalisation of a Cardiac Electrophysiology Model from Body Surface Potential Mapping, in: IEEE Transactions on Biomedical Engineering, September 2017, vol. 64, n^o 9, pp. 2206 - 2218, Selected for the TBME highlights, sept. 2017https://tbme.embs.org/2017/08/24/non-invasive-personalisation-cardiac-electrophysiology-model-body-surface-potential-mapping/. [ DOI : 10.1109/TBME.2016.2629849 ]
  https://hal.inria.fr/hal-01397393
• 18P. Gori, O. Colliot, L. Marrakchi-Kacem, Y. Worbe, C. Poupon, A. Hartmann, N. Ayache, S. Durrleman.
  A Bayesian Framework for Joint Morphometry of Surface and Curve meshes in Multi-Object Complexes, in: Medical Image Analysis, January 2017, vol. 35, pp. 458-474. [ DOI : 10.1016/j.media.2016.08.011 ]
  https://hal.inria.fr/hal-01359423
• 19B. Khanal, N. Ayache, X. Pennec.
  Simulating Longitudinal Brain MRIs with known Volume Changes and Realistic Variations in Image Intensity, in: Frontiers in Neuroscience, February 2017, vol. 11, n^o Article 132, 18 p. [ DOI : 10.3389/fnins.2017.00132 ]
  https://hal.inria.fr/hal-01348959
• 20L. Le Folgoc, H. Delingette, A. Criminisi, N. Ayache.
  Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements, in: Medical Image Analysis, February 2017, vol. 36, pp. 79 - 97. [ DOI : 10.1016/j.media.2016.09.008 ]
  https://hal.inria.fr/hal-01149544
• 21M. Lorenzi, M. Filippone, G. Frisoni, D. C. Alexander, S. Ourselin.
  Probabilistic disease progression modeling to characterize diagnostic uncertainty: application to staging and prediction in Alzheimer's disease, in: NeuroImage, October 2017.
  https://hal.archives-ouvertes.fr/hal-01617750
• 22N. Miolane, S. Holmes, X. Pennec.
  Template Shape Estimation: Correcting an Asymptotic Bias, in: SIAM Journal on Imaging Sciences, 2017, vol. 10, n^o 2, pp. 808 - 844, https://arxiv.org/abs/1610.01502. [ DOI : 10.1137/16M1084493 ]
  https://hal.archives-ouvertes.fr/hal-01350508
• 23P. 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, 2017, In press. [ DOI : 10.1093/ehjci/jex163 ]
  https://hal.inria.fr/hal-01533793
• 24R. Molléro, X. Pennec, H. Delingette, A. Garny, N. Ayache, M. Sermesant.
  Multifidelity-CMA: a multifidelity approach for efficient personalisation of 3D cardiac electromechanical models, in: Biomechanics and Modeling in Mechanobiology, September 2017, pp. 1-16. [ DOI : 10.1007/s10237-017-0960-0 ]
  https://hal.inria.fr/hal-01656008
• 25X. Pennec.
  Barycentric Subspace Analysis on Manifolds, in: Annals of Statistics, 2017, https://arxiv.org/abs/1607.02833v2, forthcoming.
  https://hal.archives-ouvertes.fr/hal-01343881
• 26N. Rodriguez-Florez, J. L. Bruse, A. Borghi, H. Vercruysse, J. Ong, G. James, X. Pennec, D. J. Dunaway, O. Jeelani, S. Schievano.
  Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty, in: International Journal of Computer Assisted Radiology and Surgery, May 2017, pp. 1-11. [ DOI : 10.1007/s11548-017-1614-5 ]
  https://hal.inria.fr/hal-01540631
• 27M.-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
• 28S. Sanchez-Martinez, N. Duchateau, T. Erdei, A. Fraser, B. Bijnens, G. Piella.
  Characterization of myocardial motion patterns by unsupervised multiple kernel learning, in: Medical Image Analysis, 2017, vol. 35, pp. 70–82. [ DOI : 10.1016/j.media.2016.06.007 ]
  https://hal.inria.fr/hal-01331550
• 29W. Schulze, Z. Chen, J. Relan, D. Potyagaylo, M. W. Krueger, R. Karim, M. Sohal, A. Shetty, Y. Ma, N. Ayache, M. Sermesant, H. Delingette, J. Bostock, R. Razavi, K. S. Rhode, C. A. Rinaldi.
  ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone, in: Medical and Biological Engineering and Computing, June 2017, vol. 55, n^o 6, pp. 979 - 990. [ DOI : 10.1007/s11517-016-1566-x ]
  https://hal.inria.fr/hal-01598299
• 30D. Soto-Iglesias, N. Duchateau, C. Butakoff, D. Andreu, J. Fernández-Armenta, B. Bijnens, A. Berruezo, M. Sitges, O. Camara.
  Quantitative analysis of electro-anatomical maps: application to an experimental model of LBBB/CRT, in: IEEE Journal of Translational Engineering in Health and Medicine, 2017, In press. [ DOI : 10.1109/JTEHM.2016.2634006 ]
  https://hal.inria.fr/hal-01398828
• 31A. 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, 2017, 13 p, In press. [ DOI : 10.1109/JBHI.2017.2652449 ]
  https://hal.inria.fr/hal-01533805
• 32Y. 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, 2017. [ DOI : 10.1109/TMI.2017.2708159 ]
  https://hal.inria.fr/hal-01533366

Invited Conferences

• 33R. Molléro, J. Hauser, X. Pennec, M. Datar, H. Delingette, A. Jones, N. Ayache, T. Heimann, M. Sermesant.
  Longitudinal Parameter Estimation in 3D Electromechanical Models: Application to Cardiovascular Changes in Digestion, in: FIMH 2017 - 9th international conference on Functional Imaging and Modeling of the Heart, Toronto, Canada, Functional Imaging and Modelling of the Heart, Springer International Publishing, June 2017, pp. 432-440. [ DOI : 10.1007/978-3-319-59448-4_41 ]
  https://hal.inria.fr/hal-01522598

International Conferences with Proceedings

• 34N. Cedilnik, J. Duchateau, R. Dubois, P. Jaïs, H. Cochet, M. Sermesant.
  VT Scan: Towards an Efficient Pipeline from Computed Tomography Images to Ventricular Tachycardia Ablation, in: Functional Imaging and Modelling of the Heart, Toronto, Canada, Functional Imaging and Modelling of the Heart, Springer International Publishing, June 2017, pp. 271-279. [ DOI : 10.1007/978-3-319-59448-4_26 ]
  https://hal.inria.fr/hal-01498672
• 35L. Devilliers, X. Pennec, S. Allassonnière.
  Inconsistency of Template Estimation with the Fréchet mean in Quotient Space, in: Information Processing in Medical Imaging 2017, Boone, United States, Information Processing in Medical Imaging: 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings, Martin Styner and Marc Niethammer and Dinggang Shen and Stephen Aylward and Ipek Oguz and Hongtu Zhu, June 2017, 12 p, https://arxiv.org/abs/1703.01232. [ DOI : 10.1007/978-3-319-59050-9_2 ]
  https://hal.inria.fr/hal-01481074
• 36R. Doste, D. Soto-Iglesias, G. Bernardino, R. Sebastian, S. Giffard-Roisin, R. Cabrera-Lozoya, M. Sermesant, A. Berruezo, D. Sánchez-Quintana, O. Camara.
  A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias, in: Functional imaging and modelling of the heart 2017, Toronto, Canada, Lecture Notes in Computer Science, June 2017, vol. 10263. [ DOI : 10.1007/978-3-319-59448-4_33 ]
  https://hal.inria.fr/hal-01533389
• 38S. Jia, C. Camaioni, M.-M. Rohé, P. Jaïs, X. Pennec, H. Cochet, M. Sermesant.
  Prediction of Post-Ablation Outcome in Atrial Fibrillation Using Shape Parameterization and Partial Least Squares Regression, in: FIMH 2017 - International Conference on Functional Imaging and Modeling of the Heart, Toronto, Canada, Lecture Notes in Computer Science, June 2017, vol. 10263, pp. 314 - 321. [ DOI : 10.1007/978-3-319-59448-4_30 ]
  https://hal.inria.fr/hal-01574831
• 39J. Krebs, T. Mansi, H. Delingette, L. Zhang, F. C. Ghesu, S. Miao, A. Maier, N. Ayache, R. Liao, A. Kamen.
  Robust non-rigid registration through agent-based action learning, in: Medical Image Computing and Computer Assisted Interventions (MICCAI), Quebec, Canada, Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, Springer International Publishing, September 2017, pp. 344-352. [ DOI : 10.1007/978-3-319-66182-7_40 ]
  https://hal.inria.fr/hal-01569447
• 40E. Lluch, R. Doste, S. Giffard-Roisin, A. This, M. Sermesant, O. Camara, M. De Craene, H. G. Morales.
  Smoothed Particle Hydrodynamics for Electrophysiological Modeling: An Alternative to Finite Element Methods, in: Functional imaging and modelling of the heart 2017, Toronto, Canada, Functional imaging and modelling of the heart 2017 Proceedings, Springer International Publishing, June 2017, vol. 141, pp. 333-343. [ DOI : 10.1007/978-3-319-59448-4_32 ]
  https://hal.inria.fr/hal-01533371
• 41K. Mcleod, M. Sermesant, X. Pennec.
  Improving Understanding of Long-Term Cardiac Functional Remodelling via Cross-Sectional Analysis of Polyaffine Motion Parameters, in: FIMH 2017 - 9th International Conference on Functional Imaging and Modeling of the Heart, Toronto, Canada, Lecture Notes in Computer Science, Springer, June 2017, vol. 10263, pp. 51 - 59. [ DOI : 10.1007/978-3-319-59448-4_6 ]
  https://hal.inria.fr/hal-01574837
• 42R. Molléro, H. Delingette, M. Datar, T. Heimann, J. Hauser, D. Panesar, A. Jones, A. Taylor, M. Kelm, T. Kuehne, M. Chinali, G. Rinelli, N. Ayache, X. Pennec, M. Sermesant.
  Longitudinal Analysis using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies, in: Medical Image Computing and Computer Assisted Intervention (MICCAI), Québec City, Canada, Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, Springer International Publishing, September 2017, pp. 350-358. [ DOI : 10.1007/978-3-319-66185-8_40 ]
  https://hal.inria.fr/hal-01569735
• 43X. Pennec.
  Sample-limited L p Barycentric Subspace Analysis on Constant Curvature Spaces, in: Geometric Sciences of Information (GSI 2017), Paris, France, Geometric Science of Information, Springer International Publishing, November 2017, pp. 20-28. [ DOI : 10.1007/978-3-319-68445-1_3 ]
  https://hal.inria.fr/hal-01574895
• 44M.-M. Rohé, M. Datar, T. Heimann, M. Sermesant, X. Pennec.
  SVF-Net: Learning Deformable Image Registration Using Shape Matching, in: MICCAI 2017 - the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, Québec, Canada, Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, Springer International Publishing, September 2017, pp. 266-274. [ DOI : 10.1007/978-3-319-66182-7_31 ]
  https://hal.inria.fr/hal-01557417
• 45M.-M. Rohé, M. Sermesant, X. Pennec.
  Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net, in: Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop, Québec, Canada, September 2017.
  https://hal.inria.fr/hal-01575297

Scientific Books (or Scientific Book chapters)

• 46S. Marchesseau, S. Chatelin, H. Delingette.
  Non linear Biomechanical Model of the Liver: Hyperelastic Constitutive Laws for Finite Element Modeling, in: Biomechanics of Living Organs, Y. Payan, J. Ohayon (editors), Elsevier, June 2017, 602 p.
  https://hal.inria.fr/hal-01536406

Scientific Popularization

• 47N. Miolane.
  Les maths de l’espace-temps qui décrivent et dépassent le cerveau, in: Interstices, February 2017.
  https://hal.inria.fr/hal-01503822

Patents

• 48H. Cochet, P. Jaïs, M. Sermesant.
  Méthode de segmentation d’une image tridimensionnelle pour la génération d’un modèle de paroi du myocarde pour la détection d’au moins une zone de circulation électrique singulière, May 2017, n^o FR1754107.
  https://hal.inria.fr/hal-01576064

Other Publications

• 49N. Miolane, S. Holmes, X. Pennec.
  Topologically constrained template estimation via Morse-Smale complexes controls its statistical consistency, December 2017, working paper or preprint.
  https://hal.inria.fr/hal-01655366
• 50A. Schmutz, J. Jacques, C. Bouveyron, L. Cheze, P. Martin.
  Clustering multivariate functional data in group-specific functional subspaces, November 2017, working paper or preprint.
  https://hal.inria.fr/hal-01652467

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