L. Antiga and B. Ene-iordache, Centerline computation and geometric analysis of branching tubular surfaces with application to blood vessel modeling, Proc. of WSCG, Int. Conf. on Computer Graphics, Visualization and Computer Vision. p. 4 pages, 2003.

J. Bano, Registration of Preoperative Liver Model for Laparoscopic Surgery from Intraoperative 3D Acquisition, Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics) LNCS, vol.8090, pp.201-210, 2013.
DOI : 10.1007/978-3-642-40843-4_22

C. Benckert and C. Bruns, The Surgeon's Contribution to Image-Guided Oncology, Viszeralmedizin, vol.30, issue.4, pp.232-236, 2014.
DOI : 10.1159/000366458

URL : https://www.karger.com/Article/Pdf/366458

D. Boltcheva, M. Yvinec, and J. Boissonnat, Mesh Generation from 3D Multi-material Images, MICCAI, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.283-90, 2009.
DOI : 10.1007/978-3-642-04271-3_35

URL : https://hal.archives-ouvertes.fr/inria-00420228

K. Brock, Accuracy of finite element model-based multi-organ deformable image registration, Medical Physics, vol.47, issue.6Part1, p.1647, 2005.
DOI : 10.1088/0031-9155/47/17/309

D. M. Cash, Compensating for intraoperative soft-tissue deformations using incomplete surface data and finite elements, IEEE Transactions on Medical Imaging, vol.24, issue.11, pp.1479-1491, 2005.
DOI : 10.1109/TMI.2005.855434

M. Chan, C. L. Chiang, V. Lee, S. Cheung, R. Leung et al., Target localization of 3D versus 4D cone beam computed tomography in lipiodol-guided stereotactic radiotherapy of hepatocellular carcinomas, PLOS ONE, vol.86, issue.4, p.174929, 2017.
DOI : 10.1371/journal.pone.0174929.t001

A. Charnoz, Liver Registration for the Follow-Up of Hepatic Tumors, Medical Image Computing and Computer-Assisted Intervention? MICCAI 2005, pp.155-162, 2005.
DOI : 10.1007/11566489_20

URL : https://hal.archives-ouvertes.fr/inria-00616006

Y. Chen, Non-rigid MR-CT Image Registration for MR-Guided Liver Cancer Surgery, 2007 IEEE/ICME International Conference on Complex Medical Engineering, pp.1756-1760, 2007.
DOI : 10.1109/ICCME.2007.4382049

C. L. Cheung, Fused Video and Ultrasound Images for Minimally Invasive Partial Nephrectomy: A Phantom Study, Medical Image Computing and Computer-Assisted Intervention?MICCAI 2010, pp.408-415, 2010.
DOI : 10.1007/978-3-642-15711-0_51

URL : https://link.springer.com/content/pdf/10.1007%2F978-3-642-15711-0_51.pdf

P. F. Christ, F. Ettlinger, F. Grün, M. E. Elshaera, J. Lipkova et al., Automatic liver and tumor segmentation of ct and mri volumes using cascaded fully convolutional neural networks, 2017.

L. W. Clements, W. C. Chapman, B. M. Dawant, R. L. Galloway-jr, and M. I. Miga, Robust surface registration using salient anatomical features for image-guided liver surgery: Algorithm and validation, Medical Physics, vol.61, issue.7, pp.2528-2540, 2008.
DOI : 10.1006/cviu.1995.1014

URL : http://europepmc.org/articles/pmc2809726?pdf=render

L. W. Clements, J. A. Collins, J. A. Weis, A. L. Simpson, L. B. Adams et al., Evaluation of model-based deformation correction in image-guided liver surgery via tracked intraoperative ultrasound, Journal of Medical Imaging, vol.3, issue.1, pp.15003-015003, 2016.
DOI : 10.1117/1.JMI.3.1.015003

URL : http://europepmc.org/articles/pmc4804127?pdf=render

W. R. Crum, Non-rigid image registration: theory and practice, The British Journal of Radiology, vol.77, issue.suppl_2, pp.140-153, 2004.
DOI : 10.1016/S1076-6332(03)00537-3

W. R. Crum, T. Hartkens, and D. Hill, Non-rigid image registration: theory and practice, The British Journal of Radiology, vol.77, issue.suppl_2, pp.140-153, 2014.
DOI : 10.1016/S1076-6332(03)00537-3

F. De-manuel, Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd???EOB???DTPA-enhanced MRI, Medical Image Analysis, vol.18, issue.1, pp.22-35, 2014.
DOI : 10.1016/j.media.2013.09.002

T. R. Dos-santos, Pose-independent surface matching for intra-operative soft-tissue marker-less registration, Medical Image Analysis, vol.18, issue.7, pp.1101-1114, 2014.
DOI : 10.1016/j.media.2014.06.002

C. L. Eccles, V. T. Regina, M. A. Hawkins, M. T. Lee, D. J. Moseley et al., Intravenous contrast-enhanced cone beam computed tomography (IVCBCT) of intrahepatic tumors and vessels, Advances in Radiation Oncology, vol.1, issue.1, pp.43-50, 2016.
DOI : 10.1016/j.adro.2016.01.001

URL : https://doi.org/10.1016/j.adro.2016.01.001

E. Eisenhauer, New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1), European Journal of Cancer, vol.45, issue.2, pp.228-247, 2009.
DOI : 10.1016/j.ejca.2008.10.026

H. Elhawary, Multimodality Non-rigid Image??Registration for Planning, Targeting and Monitoring During CT-Guided Percutaneous Liver Tumor Cryoablation, Academic Radiology, vol.17, issue.11, pp.1334-1344, 2010.
DOI : 10.1016/j.acra.2010.06.004

URL : http://europepmc.org/articles/pmc2952665?pdf=render

A. Enquobahrie, L. Ibanez, E. Bullitt, and S. Aylward, Vessel enhancing diffusion filter, The Insight Journal, vol.1, pp.1-14, 2007.

F. Faure, C. Duriez, H. Delingette, J. Allard, B. Gilles et al., SOFA: A Multi-Model Framework for Interactive Physical Simulation, pp.283-321, 2012.
DOI : 10.1007/8415_2012_125

URL : https://hal.archives-ouvertes.fr/hal-00681539

L. Feldkamp, L. Davis, and J. Kress, Practical cone-beam algorithm, Journal of the Optical Society of America A, vol.1, issue.6, pp.612-619, 1984.
DOI : 10.1364/JOSAA.1.000612

URL : http://www.engineering.uiowa.edu/~mchen/reconstruction/practical feldkamp.pdf

A. H. Foruzan and H. R. Motlagh, Multimodality liver registration of Open-MR and CT scans, International Journal of Computer Assisted Radiology and Surgery, vol.56, issue.6, pp.1253-1267, 2015.
DOI : 10.1109/IEMBS.2007.4352425

W. E. Grimson, An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization, IEEE Transactions on Medical Imaging, vol.15, issue.2, pp.129-140, 1996.
DOI : 10.1109/42.491415

O. Heizmann, Assessment of Intraoperative Liver Deformation During Hepatic Resection: Prospective Clinical Study, World Journal of Surgery, vol.8, issue.8, pp.1887-93, 2010.
DOI : 10.1007/s00268-010-0561-x

D. L. Hill, Medical image registration, Physics in Medicine and Biology, vol.46, issue.3, p.1, 2001.
DOI : 10.1088/0031-9155/46/3/201

URL : https://hal.archives-ouvertes.fr/inria-00615977

T. Ikeda, Y. Mano, K. Morita, N. Hashimoto, H. Kayashima et al., Pure laparoscopic hepatectomy in semiprone position for right hepatic major resection, Journal of Hepato-Biliary-Pancreatic Sciences, vol.7, issue.12, pp.145-150, 2013.
DOI : 10.1007/s005340070007

URL : http://onlinelibrary.wiley.com/doi/10.1007/s00534-012-0558-y/pdf

W. Jarnagin, A. L. Simpson, and M. Miga, Toward integrated image guided liver surgery, SPIE Medical Imaging. International Society for Optics and Photonics, pp.101350-101350, 2017.
DOI : 10.1117/12.2257615

B. L. Jones, C. Altunbas, B. Kavanagh, T. Schefter, and M. Miften, Optimized dynamic contrast-enhanced cone-beam CT for target visualization during liver SBRT, Journal of Physics: Conference Series, vol.489, p.12035, 2014.
DOI : 10.1088/1742-6596/489/1/012035

URL : http://iopscience.iop.org/article/10.1088/1742-6596/489/1/012035/pdf

M. R. Kaus, Assessment of a Model-Based Deformable Image Registration Approach for Radiation Therapy Planning, International Journal of Radiation Oncology*Biology*Physics, vol.68, issue.2, pp.572-580, 2007.
DOI : 10.1016/j.ijrobp.2007.01.056

H. G. Kenngott, M. Wagner, M. Gondan, F. Nickel, M. Nolden et al., Real-time image guidance in laparoscopic liver surgery: first clinical experience with a guidance system based on intraoperative CT imaging, Surgical Endoscopy, vol.83, issue.1, pp.933-940
DOI : 10.1016/j.ijrobp.2011.12.007

F. Khalifa, State-of-the-art medical image registration methodologies: a survey In: Multi modality state-of-the-art medical image segmentation and registration methodologies, pp.235-280, 2011.

T. Lange, Validation Metrics for Non-rigid Registration of Medical Images Containing Vessel Trees, In: Bildverarbeitung für die Medizin, pp.82-86, 2008.
DOI : 10.1007/978-3-540-78640-5_17

C. P. Lee, Evaluation of Five Image Registration Tools for Abdominal CT: Pitfalls and Opportunities with Soft Anatomy, SPIE Medical Imaging. International Society for Optics and Photonics, pp.94131-94131, 2015.
DOI : 10.1117/12.2081045

URL : http://europepmc.org/articles/pmc4405654?pdf=render

D. Li, L. Liu, J. Chen, and H. Li, SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction, Medical Physics, vol.41, issue.6Part6, pp.150-150, 2014.
DOI : 10.1118/1.4888037

D. W. Li, H. J. Wang, D. Chen, and Y. Yin, Automated Liver Segmentation for Cone Beam CT Dataset by Probabilistic Atlas Construction, Applied Mechanics and Materials, vol.195, issue.196, pp.583-588, 2012.
DOI : 10.4028/www.scientific.net/AMM.195-196.583

J. A. Maintz and M. A. Viergever, A survey of medical image registration, Medical Image Analysis, vol.2, issue.1, pp.1-36, 1998.
DOI : 10.1016/S1361-8415(01)80026-8

B. Marami, S. Sirouspour, and D. Capson, Model-based deformable registration of preoperative 3D to intraoperative low-resolution 3D and 2D sequences of MR images. MICCAI, pp.460-467, 2011.

S. Marchesseau, T. Heimann, S. Chatelin, R. Willinger, and H. Delingette, Fast porous visco-hyperelastic soft tissue model for surgery simulation: Application to liver surgery, Progress in biophysics and molecular biology, pp.185-96, 2010.
DOI : 10.1016/j.pbiomolbio.2010.09.005

URL : https://hal.archives-ouvertes.fr/hal-00593223

D. Mattes, PET-CT image registration in the chest using free-form deformations, IEEE Transactions on Medical Imaging, vol.22, issue.1, pp.120-128, 2003.
DOI : 10.1109/TMI.2003.809072

H. Meinzer, M. Thorn, and C. E. Cárdenas, Computerized planning of liver surgery???an overview, Computers & Graphics, vol.26, issue.4, pp.569-576, 2002.
DOI : 10.1016/S0097-8493(02)00102-4

M. Modat, A parallel-friendly normalized mutual information gradient for free-form registration, Medical Imaging 2009: Image Processing, pp.72590-72590, 2009.
DOI : 10.1117/12.811588

M. Modat, Fast free-form deformation using graphics processing units, Computer Methods and Programs in Biomedicine, vol.98, issue.3, pp.278-84, 2010.
DOI : 10.1016/j.cmpb.2009.09.002

URL : http://eprints.ucl.ac.uk/17431/1/17431.pdf

M. Mulholland, M. T. Hawn, S. Hughes, D. Albo, M. Sabel et al., Operative Techniques in Surgery, 2014.

M. Müller, Stable real-time deformations, Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation , SCA '02, 2002.
DOI : 10.1145/545261.545269

, ACM, pp.49-54

K. Murphy, Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge, IEEE Transactions on Medical Imaging, vol.30, issue.11, pp.1901-1920, 2011.
DOI : 10.1109/TMI.2011.2158349

URL : https://hal.archives-ouvertes.fr/inserm-00607794

M. Nesme, Y. Payan, and F. Faure, Efficient, physically plausible finite elements, Eurographics 2005, pp.77-80, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00394480

S. Nicolau, L. Soler, D. Mutter, and J. Marescaux, Augmented reality in laparoscopic surgical oncology, Surgical Oncology, vol.20, issue.3, pp.189-201, 2011.
DOI : 10.1016/j.suronc.2011.07.002

J. Nocedal and S. Wright, Numerical Optimization. Springer Series in Operations Research and Financial Engineering, 2006.

O. Oktay, Biomechanically driven registration of pre-to intraoperative 3D images for laparoscopic surgery, Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), issue.2, pp.8150-8151, 2013.

I. Peterlik, M. Nouicer, C. Duriez, S. Cotin, and A. Kheddar, Constraint-Based Haptic Rendering of Multirate Compliant Mechanisms, IEEE Transactions on Haptics, vol.4, issue.3, pp.175-187, 2011.
DOI : 10.1109/TOH.2011.41

URL : https://hal.archives-ouvertes.fr/lirmm-00784081

R. Plantefève, Patient-Specific Biomechanical Modeling for Guidance During Minimally-Invasive Hepatic Surgery, Annals of Biomedical Engineering, vol.31, issue.3, pp.139-153, 2016.
DOI : 10.1016/j.neuroimage.2006.01.015

K. Popuri, D. Cobzas, and M. Jagerstand, Fast FEM-Based Non-Rigid Registration, 2010 Canadian Conference on Computer and Robot Vision, pp.378-385, 2010.
DOI : 10.1109/CRV.2010.56

I. Reinertsen, F. Lindseth, G. Unsgaard, and D. Collins, Clinical validation of vessel-based registration for correction of brain-shift, Medical Image Analysis, vol.11, issue.6, pp.673-684, 2007.
DOI : 10.1016/j.media.2007.06.008

C. Rieder, Automatic alignment of pre- and post-interventional liver CT images for assessment of radiofrequency ablation, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, pp.83163-83163, 2012.
DOI : 10.1117/12.911188

T. Rohlfing and C. R. Maurer-jr, Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees, IEEE Transactions on Information Technology in Biomedicine, vol.7, issue.1, pp.16-25, 2003.
DOI : 10.1109/TITB.2003.808506

T. Rohlfing, Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint, IEEE Transactions on Medical Imaging, vol.22, issue.6, pp.730-741, 2003.
DOI : 10.1109/TMI.2003.814791

J. Rohrer, L. Gong, and G. Székely, Parallel mutual information based 3D non-rigid registration on a multi-core platform, High-Performance MIC- CAI workshop, p.12, 2008.

L. Ru?ka and I. Peterlík, Fast reconstruction of image deformation field using radial basis function, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp.1146-1150, 2017.
DOI : 10.1109/ISBI.2017.7950719

D. C. Rucker, A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data, IEEE Transactions on Medical Imaging, vol.33, issue.1, pp.1-12, 2013.
DOI : 10.1109/TMI.2013.2283016

D. C. Rucker, Nonrigid liver registration for image-guided surgery using partial surface data: a novel iterative approach, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, pp.86710-86710, 2013.
DOI : 10.1117/12.2007991

D. Rueckert and P. Aljabar, Non-rigid registration using free-form deformations, pp.277-294, 2015.
DOI : 10.1007/978-0-387-09749-7_15

D. Rueckert, Nonrigid registration using free-form deformations: application to breast MR images, IEEE Transactions on Medical Imaging, vol.18, issue.8, pp.712-721, 1999.
DOI : 10.1109/42.796284

S. Rusinkiewicz and M. Levoy, Efficient variants of the ICP algorithm, Proceedings Third International Conference on 3-D Digital Imaging and Modeling, pp.145-152, 2001.
DOI : 10.1109/IM.2001.924423

G. Sharp, N. Kandasamy, H. Singh, and M. Folkert, GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration, Physics in Medicine and Biology, vol.52, issue.19, p.5771, 2007.
DOI : 10.1088/0031-9155/52/19/003

R. Shekhar, Live augmented reality: a new visualization method for laparoscopic surgery using continuous volumetric computed tomography, Surgical Endoscopy, vol.206, issue.8, pp.1976-1985, 2010.
DOI : 10.1007/s00464-010-0890-8

A. L. Simpson, Model-Assisted Image-Guided Liver Surgery Using Sparse Intraoperative Data, pp.7-40, 2012.
DOI : 10.1007/8415_2012_117

H. Song, Multi-modality liver image registration based on multilevel B-splines free-form deformation and L-BFGS optimal algorithm, Journal of Central South University, vol.76, issue.10, pp.287-292, 2014.
DOI : 10.1016/j.neuroimage.2013.03.015

A. Sotiras, C. Davatzikos, and N. Paragios, Deformable Medical Image Registration: A Survey, IEEE Transactions on Medical Imaging, vol.32, issue.7, pp.1153-1190, 2013.
DOI : 10.1109/TMI.2013.2265603

URL : https://hal.archives-ouvertes.fr/hal-00684715

S. Speidel, Intraoperative surface reconstruction and biomechanical modeling for soft tissue registration, Scath.Net, pp.1-4, 2011.

S. M. Strasberg, Nomenclature of hepatic anatomy and resections: a review of the Brisbane 2000 system, Journal of Hepato-Biliary-Pancreatic Surgery, vol.4, issue.5, pp.351-355, 2005.
DOI : 10.1001/archsurg.1953.01260030616008

S. Suwelack, S. Röhl, S. Bodenstedt, D. Reichard, R. Dillmann et al., Physics-based shape matching for intraoperative image guidance, Medical Physics, vol.27, issue.4, pp.41-111901, 2014.
DOI : 10.1118/1.4896021.1

S. Suwelack, Quadratic Corotated Finite Elements for Real-Time Soft Tissue Registration, Computational Biomechanics for Medicine, pp.39-50, 2012.
DOI : 10.1007/978-1-4614-3172-5_6

S. Tang and Y. Wang, MR-guided liver cancer surgery by nonrigid registration, In: Int. Conf. on Med. Image Anal. and Clinical Applications, pp.113-117, 2010.

P. Thévenaz and M. Unser, Optimization of mutual information for multiresolution image registration, IEEE Trans. on Image Processing, vol.9, issue.12, pp.2083-2099, 2000.

N. Tsutsumi, Image-guided laparoscopic surgery in an open MRI operating theater, Surgical Endoscopy, vol.43, issue.6, pp.2178-2184, 2013.
DOI : 10.1016/j.jbiomech.2010.01.013

M. Uchida, Recent advances in 3D computed tomography techniques for simulation and navigation in hepatobiliary pancreatic surgery, Journal of Hepato-Biliary-Pancreatic Sciences, vol.251, issue.4, pp.239-245, 2014.
DOI : 10.1148/radiol.2513081330

URL : http://onlinelibrary.wiley.com/doi/10.1002/jhbp.82/pdf

B. Vagvolgyi, L. Su, R. Taylor, and G. Hager, Video to CT registration for image overlay on solid organs, Proc. Augmented Reality in Medical Imaging and Augmented Reality in Computer-Aided Surgery (AMIARCS), pp.78-86, 2008.

L. Verscheure, Three-dimensional skeletonization and symbolic description in vascular imaging: preliminary results, International Journal of Computer Assisted Radiology and Surgery, vol.18, issue.4, pp.233-246, 2013.
DOI : 10.1016/j.acra.2010.11.015

URL : https://hal.archives-ouvertes.fr/hal-01181350

G. Wakabayashi, D. Cherqui, D. A. Geller, J. F. Buell, H. Kaneko et al., Recommendations for laparoscopic liver resection: a report from the second international consensus conference held in morioka, Annals of surgery, vol.261, issue.4, pp.619-629, 2015.

A. Wittek, T. Hawkins, and K. Miller, On the unimportance of constitutive models in computing brain deformation for image-guided surgery, Biomechanics and Modeling in Mechanobiology, vol.5, issue.1, pp.77-84, 2009.
DOI : 10.1115/1.3426188

Y. Wu, Registration of liver images to minimally invasive intraoperative surface and subsurface data, SPIE Medical Imaging. International Society for Optics and Photonics, pp.90360-90360, 2014.
DOI : 10.1117/12.2044250

URL : http://etd.library.vanderbilt.edu/available/etd-03272014-152811/unrestricted/YifeiWu.pdf

P. A. Yushkevich, User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability, NeuroImage, vol.31, issue.3, pp.1116-1128, 2006.
DOI : 10.1016/j.neuroimage.2006.01.015

URL : http://midag.cs.unc.edu/pubs/papers/Neuroimage06_Yushkevich.pdf