D. Angelova and L. Mihaylova, Contour segmentation in 2d ultrasound medical images with particle filtering. Machine Vision and Applications, pp.551-561, 2010.

S. Baker and I. Matthews, Lucas-Kanade 20 Years On: A Unifying Framework, International Journal of Computer Vision, vol.56, issue.3, pp.221-255, 2004.
DOI : 10.1023/B:VISI.0000011205.11775.fd

J. Banerjee, C. Klink, E. D. Peters, W. J. Niessen, A. Moelker et al., Fast and robust 3D ultrasound registration ??? Block and game theoretic matching, Medical Image Analysis, vol.20, issue.1, pp.173-183, 2015.
DOI : 10.1016/j.media.2014.11.004

D. Barbosa, D. Friboulet, J. D-'hooge, and O. Bernard, Fast tracking of the left ventricle using global anatomical affine optical flow and local recursive block matching, Proc. of the MICCAI Challenge on Endocardial Three-dimensional Ultrasound Segmentation-CETUS, pp.17-24, 2014.

A. Basarab, H. Liebgott, F. Morestin, A. Lyshchik, T. Higashi et al., A method for vector displacement estimation with ultrasound imaging and its application for thyroid nodular disease, Medical Image Analysis, vol.12, issue.3, pp.259-274, 2008.
DOI : 10.1016/j.media.2007.10.007

M. Baumann, P. Mozer, V. Daanen, and J. Troccaz, Prostate biopsy tracking with deformation estimation, Medical Image Analysis, vol.16, issue.3, pp.562-576, 2012.
DOI : 10.1016/j.media.2011.01.008
URL : https://hal.archives-ouvertes.fr/hal-00606407

M. A. Bell, B. C. Byram, E. J. Harris, P. M. Evans, and J. C. Bamber, liver tracking with a high volume rate 4D ultrasound scanner and a 2D matrix array probe, Physics in Medicine and Biology, vol.57, issue.5, pp.1359-1374, 2012.
DOI : 10.1088/0031-9155/57/5/1359

C. S. Berge, A. Kapoor, and N. Navab, Orientation-Driven Ultrasound Compounding Using Uncertainty Information, Proc. of International Conference on Information Processing in Computer-Assisted Interventions, pp.236-245, 2014.
DOI : 10.1007/978-3-319-07521-1_25

F. L. Bookstein, Principal warps: thin-plate splines and the decomposition of deformations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.6, pp.567-585, 1989.
DOI : 10.1109/34.24792

S. Chagnon, S. Qanadli, L. , and P. , Destruction percutanée des tumeurs du foie par radiofréquence, Gastroentérologie clinique et biologique, vol.25, pp.85-99, 2001.

R. Chang, W. Wu, W. K. Moon, C. , and D. , Automatic ultrasound segmentation and morphology based diagnosis of solid breast tumors, Breast Cancer Research and Treatment, vol.226, issue.2, pp.179-185, 2005.
DOI : 10.1007/s10549-004-2043-z

P. Chatelain, A. Krupa, and N. Navab, Optimization of ultrasound image quality via visual servoing, 2015 IEEE International Conference on Robotics and Automation (ICRA), pp.5997-6002, 2015.
DOI : 10.1109/ICRA.2015.7140040
URL : https://hal.archives-ouvertes.fr/hal-01121222

G. E. Christensen and H. J. Johnson, Consistent image registration, IEEE Transactions on Medical Imaging, vol.20, issue.7, pp.568-582, 2001.
DOI : 10.1109/42.932742

B. Cohen and I. H. Dinstein, New maximum likelihood motion estimation schemes for noisy ultrasound images, Pattern Recognition, vol.35, issue.2, pp.455-463, 2002.
DOI : 10.1016/S0031-3203(01)00053-X

D. Comaniciu, X. Zhou, and S. Krishnan, Robust Real-Time Myocardial Border Tracking for Echocardiography: An Information Fusion Approach, IEEE Transactions on Medical Imaging, vol.23, issue.7, pp.849-860, 2004.
DOI : 10.1109/TMI.2004.827967

P. Coupé, P. Hellier, X. Morandi, and C. Barillot, 3D Rigid Registration of Intraoperative Ultrasound and Preoperative MR Brain Images Based on Hyperechogenic Structures, International Journal of Biomedical Imaging, vol.218, issue.2, p.1, 2012.
DOI : 10.1016/S1076-6332(03)00506-3

D. Luca, V. Székely, G. , T. , and C. , Estimation of Large-Scale Organ Motion in B-Mode Ultrasound Image Sequences: A Survey, Ultrasound in Medicine & Biology, 2015.

D. Luca, V. Tschannen, M. Székely, G. , T. et al., A learning-based approach for fast and robust vessel tracking in long ultrasound sequences, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.518-525, 2013.

B. Delabarre and E. Marchand, Dense non-rigid visual tracking with a robust similarity function, 2014 IEEE International Conference on Image Processing (ICIP), pp.4942-4946, 2014.
DOI : 10.1109/ICIP.2014.7026001
URL : https://hal.archives-ouvertes.fr/hal-00997377

T. Dietenbeck, D. Barbosa, M. Alessandrini, R. Jasaityte, V. Robesyn et al., Whole myocardium tracking in 2D-echocardiography in multiple orientations using a motion constrained level-set, Medical Image Analysis, vol.18, issue.3, pp.500-514, 2014.
DOI : 10.1016/j.media.2014.01.005
URL : https://hal.archives-ouvertes.fr/hal-00941827

A. Elen, . Hon-fai-choi, D. Loeckx, H. Gao, C. et al., Three-Dimensional Cardiac Strain Estimation Using Spatio???Temporal Elastic Registration of Ultrasound Images: A Feasibility Study, IEEE Transactions on Medical Imaging, vol.27, issue.11, pp.271580-1591, 2008.
DOI : 10.1109/TMI.2008.2004420

R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, The Computer Journal, vol.7, issue.2, pp.149-154, 1964.
DOI : 10.1093/comjnl/7.2.149
URL : https://academic.oup.com/comjnl/article-pdf/7/2/149/959725/070149.pdf

J. C. Gee, On matching brain volumes, Pattern Recognition, vol.32, issue.1, pp.99-111, 1999.
DOI : 10.1016/S0031-3203(98)00093-4

M. Gilles, H. Fayad, P. Miglierini, J. F. Clement, S. Scheib et al., Patient positioning in radiotherapy based on surface imaging using time of flight cameras, Medical Physics, vol.88, issue.8Part1, pp.434833-4841, 2016.
DOI : 10.1016/j.ijrobp.2013.09.026

N. J. Gordon, D. J. Salmond, and A. F. Smith, Novel approach to nonlinear/non-Gaussian Bayesian state estimation, Proc. of International Conference on Radar and Signal Processing, pp.107-113, 1993.
DOI : 10.1049/ip-f-2.1993.0015

T. Heimann, B. Van-ginneken, M. Styner, Y. Arzhaeva, V. Aurich et al., Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets, IEEE Transactions on Medical Imaging, vol.28, issue.8, pp.281251-1265, 2009.
DOI : 10.1109/TMI.2009.2013851

P. Hellier, P. Coupé, X. Morandi, C. , and D. L. , An automatic geometrical and statistical method to detect acoustic shadows in intraoperative ultrasound brain images, Medical Image Analysis, vol.14, issue.2, pp.195-204, 2010.
DOI : 10.1016/j.media.2009.10.007
URL : https://hal.archives-ouvertes.fr/inria-00432724

B. Heyde, P. Claus, R. Jasaityte, D. Barbosa, S. Bouchez et al., Motion and deformation estimation of cardiac ultrasound sequences using an anatomical B-spline transformation model, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.266-269, 2012.
DOI : 10.1109/ISBI.2012.6235535

H. Higgins and D. L. Berger, RFA for Liver Tumors: Does It Really Work?, The Oncologist, vol.11, issue.7, pp.801-808, 2006.
DOI : 10.1634/theoncologist.11-7-801

Y. Häme, V. Gamarnik, K. M. Parker, J. W. Holmes, L. et al., Level set-based tracking of the endocardium without a shape prior from, 2012.

Y. Hu, H. U. Ahmed, Z. Taylor, C. Allen, M. Emberton et al., MR to ultrasound registration for image-guided prostate interventions, Medical Image Analysis, vol.16, issue.3, pp.687-703, 2012.
DOI : 10.1016/j.media.2010.11.003

Y. Hu, D. Morgan, H. U. Ahmed, D. Pendsé, M. Sahu et al., A Statistical Motion Model Based on Biomechanical Simulations for Data Fusion during Image-Guided Prostate Interventions, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.737-744, 2008.
DOI : 10.1007/978-3-540-85988-8_88

M. Irani, B. Rousso, and S. Peleg, Detecting and tracking multiple moving objects using temporal integration, Proc. of European Conference on Computer Vision, pp.282-287, 1992.
DOI : 10.1007/3-540-55426-2_33

J. Jain and A. Jain, Displacement Measurement and Its Application in Interframe Image Coding, IEEE Transactions on Communications, vol.29, issue.12, pp.1799-1808, 1981.
DOI : 10.1109/TCOM.1981.1094950

S. Kadoury, L. Zagorchev, B. J. Wood, A. Venkatesan, J. Weese et al., A model-based registration approach of preoperative MRI with 3D ultrasound of the liver for Interventional guidance procedures, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.952-955, 2012.
DOI : 10.1109/ISBI.2012.6235714

R. E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, vol.82, issue.1, pp.35-45, 1960.
DOI : 10.1115/1.3662552

A. Karamalis, W. Wein, T. Klein, and N. Navab, Ultrasound confidence maps using random walks, Medical Image Analysis, vol.16, issue.6, pp.1101-1112, 2012.
DOI : 10.1016/j.media.2012.07.005

B. M. Künzli, P. Abitabile, and C. A. Maurer, Radiofrequency ablation of liver tumors: Actual limitations and potential solutions in the future, World Journal of Hepatology, vol.3, issue.1, pp.8-14, 2011.
DOI : 10.4254/wjh.v3.i1.8

M. Kuklisova-murgasova, G. Quaghebeur, J. V. Hajnal, J. A. Noble, and J. A. Schnabel, Towards 3D registration of fetal brain MRI and ultrasound, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.346-349, 2012.
DOI : 10.1109/ISBI.2012.6235555

T. Lange, N. Papenberg, S. Heldmann, J. Modersitzki, B. Fischer et al., 3D ultrasound-CT registration of the liver using combined landmark-intensity information, International Journal of Computer Assisted Radiology and Surgery, vol.1, issue.3, pp.79-88, 2008.
DOI : 10.1007/b98874

A. Lasso, T. Heffter, A. Rankin, C. Pinter, T. Ungi et al., PLUS: Open-Source Toolkit for Ultrasound-Guided Intervention Systems, IEEE Transactions on Biomedical Engineering, vol.61, issue.10, pp.612527-2537, 2014.
DOI : 10.1109/TBME.2014.2322864

M. J. Ledesma-carbayo, J. Kybic, M. Desco, A. Santos, and M. Unser, Cardiac Motion Analysis from Ultrasound Sequences Using Non-rigid Registration, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.889-896, 2001.
DOI : 10.1007/3-540-45468-3_106
URL : https://link.springer.com/content/pdf/10.1007%2F3-540-45468-3_106.pdf

M. Lediju, B. C. Byram, E. J. Harris, P. M. Evans, and J. C. Bamber, 3D Liver tracking using a matrix array: Implications for ultrasonic guidance of IMRT, 2010 IEEE International Ultrasonics Symposium, pp.1628-1631, 2010.
DOI : 10.1109/ULTSYM.2010.5935559

D. Lee and A. Krupa, Intensity-based visual servoing for non-rigid motion compensation of soft tissue structures due to physiological motion using 4D ultrasound, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2831-2836, 2011.
DOI : 10.1109/IROS.2011.6094953
URL : https://hal.archives-ouvertes.fr/hal-00639687

D. Lee, W. H. Nam, J. Y. Lee, R. , and J. B. , Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information, Physics in Medicine and Biology, vol.56, issue.1, pp.117-137, 2011.
DOI : 10.1088/0031-9155/56/1/008

D. Lubke and C. Grozea, High Performance Online Motion Tracking in Abdominal Ultrasound Imaging, Proc. of MICCAI Workshop on Challenge on Liver Ultrasound Tracking, p.29, 2014.

P. C. Mahalanobis, On the generalised distance in statistics, Proc. of the National Institute of Sciences of India, pp.49-56, 1936.

B. Marami, S. Sirouspour, A. Fenster, W. Capson, and D. , Dynamic Tracking of a Deformable Tissue Based on 3d-2d MR-US Image Registration, Proc. of SPIE Medical Imaging, pp.33-36, 2014.

M. A. Masum, M. Pickering, A. Lambert, J. Scarvell, and P. Smith, Accuracy assessment of Tri-plane B-mode ultrasound for non-invasive 3D kinematic analysis of knee joints, BioMedical Engineering OnLine, vol.13, issue.1, p.122, 2014.
DOI : 10.1016/j.sigpro.2009.04.042

C. Metz, S. Klein, M. Schaap, T. Van-walsum, and W. Niessen, Nonrigid registration of dynamic medical imaging data using nD+t B-splines and a groupwise optimization approach, Medical Image Analysis, vol.15, issue.2, pp.238-249, 2011.
DOI : 10.1016/j.media.2010.10.003

I. Mikic, S. Krucinski, T. , and J. D. , Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates, IEEE Transactions on Medical Imaging, vol.17, issue.2, pp.274-284, 1998.
DOI : 10.1109/42.700739

J. J. Moré and D. J. Thuente, Line search algorithms with guaranteed sufficient decrease, ACM Transactions on Mathematical Software, vol.20, issue.3, pp.286-307, 1994.
DOI : 10.1145/192115.192132

R. Mukherjee, C. Sprouse, T. Abraham, B. Hoffmann, E. Mcveigh et al., Myocardial motion computation in 4D ultrasound, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1070-1073, 2011.
DOI : 10.1109/ISBI.2011.5872586

J. C. Nascimento and J. S. Marques, Robust Shape Tracking With Multiple Models in Ultrasound Images, IEEE Transactions on Image Processing, vol.17, issue.3, pp.392-406, 2008.
DOI : 10.1109/TIP.2007.915552

F. Nazem, A. Ahmadian, N. D. Seraj, and M. Giti, Two-stage point-based registration method between ultrasound and CT imaging of the liver based on ICP and unscented Kalman filter: a phantom study, International Journal of Computer Assisted Radiology and Surgery, vol.11, issue.4, 2013.
DOI : 10.1016/j.media.2007.04.002

D. Ni, Y. Qu, X. Yang, Y. P. Chui, T. Wong et al., Volumetric Ultrasound Panorama Based on 3D SIFT, Proc. of Medical Image Computing and Computer-Assisted Intervention, pp.52-60, 2008.
DOI : 10.1109/42.906424

J. Nickolls, I. Buck, M. Garland, and K. Skadron, Scalable parallel programming with CUDA, Queue, vol.6, issue.2, pp.40-53, 2008.
DOI : 10.1145/1365490.1365500

F. Orderud, J. Hansg\a-ard, and S. I. And-rabben, Real-Time Tracking of the Left Ventricle in 3D Echocardiography Using a State Estimation Approach, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.858-865, 2007.
DOI : 10.1007/978-3-540-75757-3_104

S. Osher and R. P. Fedkiw, Level set methods and dynamic implicit surfaces. Applied mathematical science, 2003.
DOI : 10.1115/1.1760520

X. Papademetris, A. Sinusas, D. Dione, R. Constable, D. et al., Estimation of 3-D left ventricular deformation from medical images using biomechanical models, IEEE Transactions on Medical Imaging, vol.21, issue.7, pp.786-800, 2002.
DOI : 10.1109/TMI.2002.801163

X. Pennec, P. Cachier, and N. Ayache, Tracking brain deformations in timesequences of 3d US images, Proc. of International Conference on Information Processing in Medical Imaging, pp.169-175, 2001.
URL : https://hal.archives-ouvertes.fr/inria-00072541

G. Penney, J. Blackall, M. Hamady, T. Sabharwal, A. Adam et al., Registration of freehand 3D ultrasound and magnetic resonance liver images, Medical Image Analysis, vol.8, issue.1, pp.81-91, 2004.
DOI : 10.1016/j.media.2003.07.003

M. R. Pickering, A. Muhit, J. M. Scarvell, and P. N. Smith, A new multimodal similarity measure for fast gradient-based 2d-3d image registration, Proc. of IEEE International Conference on Engineering in Medicine and Biology, pp.5821-5824, 2009.

R. Richa, M. Souza, G. Scandaroli, E. Comunello, V. Wangenheim et al., Direct visual tracking under extreme illumination variations using the sum of conditional variance, 2014 IEEE International Conference on Image Processing (ICIP), pp.373-377, 2014.
DOI : 10.1109/ICIP.2014.7025074

R. Richa, R. Sznitman, R. Taylor, and G. Hager, Visual tracking using the sum of conditional variance, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2953-2958, 2011.
DOI : 10.1109/IROS.2011.6094650

A. Roche, X. Pennec, G. Malandain, and N. Ayache, Rigid registration of 3-D ultrasound with MR images: a new approach combining intensity and gradient information, IEEE Transactions on Medical Imaging, vol.20, issue.10, pp.201038-1049, 2001.
DOI : 10.1109/42.959301
URL : https://hal.archives-ouvertes.fr/cea-00333699

S. Rothlubbers, J. Schwaab, J. Jenne, and M. Gunther, MICCAI CLUST 2014- Bayesian Real-Time Liver Feature Ultrasound Tracking, Proc. of MICCAI Workshop on Challenge on Liver Ultrasound Tracking, p.45, 2014.

L. Royer, M. Marchal, L. Bras, A. Dardenne, G. Krupa et al., Real-time tracking of deformable target in 3D ultrasound images, 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015.
DOI : 10.1109/ICRA.2015.7139523
URL : https://hal.archives-ouvertes.fr/hal-01122026

S. Salles, G. Zahnd, H. Liebgott, A. Serusclat, and D. Vray, Real time US-tagging combined with phase-based optical flow applied to 2D motion estimation of the carotid artery wall, 2012 IEEE International Ultrasonics Symposium, pp.1185-1188, 2012.
DOI : 10.1109/ULTSYM.2012.0295
URL : https://hal.archives-ouvertes.fr/hal-00840399

R. J. Schneider, D. P. Perrin, N. V. Vasilyev, G. R. Marx, P. J. Del-nido et al., Real-time image-based rigid registration of three-dimensional ultrasound, Medical Image Analysis, vol.16, issue.2, pp.402-414, 2012.
DOI : 10.1016/j.media.2011.10.004

W. Schroeder, K. W. Martin, and B. Lorensen, The Visualization Toolkit, 2002.
DOI : 10.1016/B978-012387582-2/50032-0

T. W. Sederberg and S. R. Parry, Free-form deformation of solid geometric models, ACM SIGGRAPH Computer Graphics, vol.20, issue.4, pp.151-160, 1986.
DOI : 10.1145/15886.15903

J. Seo, N. Koizumi, T. Funamoto, N. Sugita, K. Yoshinaka et al., Visual servoing for a US-guided therapeutic HIFU system by coagulated lesion tracking: a phantom study, The International Journal of Medical Robotics and Computer Assisted Surgery, vol.49, issue.2, pp.237-247, 2011.
DOI : 10.1088/0031-9155/49/3/006

R. Shekhar and V. Zagrodsky, Mutual information-based rigid and nonrigid registration of ultrasound volumes, IEEE Transactions on Medical Imaging, vol.21, issue.1, pp.9-22, 2002.
DOI : 10.1109/42.981230

H. Si, TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator, ACM Transactions on Mathematical Software, vol.41, issue.2, p.41, 2015.
DOI : 10.1016/0925-7721(95)00040-2

O. Somphone, S. Allaire, B. Mory, and C. Dufour, Live Feature Tracking in Ultrasound Liver Sequences with Sparse Demons, Proc. of MICCAI Workshop on Challenge on Liver Ultrasound Tracking, p.53, 2014.

A. Sotiras, C. Davatzikos, P. , and N. , 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

C. Tanner, J. A. Schnabel, D. Chung, M. J. Clarkson, D. Rueckert et al., Volume and Shape Preservation of Enhancing Lesions when Applying Non-rigid Registration to a Time Series of Contrast Enhancing MR Breast Images, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.327-337, 2000.
DOI : 10.1007/978-3-540-40899-4_33

L. A. Torre, F. Bray, R. L. Siegel, J. Ferlay, J. Lortet-tieulent et al., Global cancer statistics, 2012, CA: A Cancer Journal for Clinicians, vol.6, issue.19, pp.87-108, 2012.
DOI : 10.1038/nrc1948

B. Touil, A. Basarab, P. Delachartre, O. Bernard, and D. Friboulet, Analysis of motion tracking in echocardiographic image sequences: Influence of system geometry and point-spread function, Ultrasonics, vol.50, issue.3, pp.50373-386, 2010.
DOI : 10.1016/j.ultras.2009.09.001

M. Uhercik, H. Liebgott, J. Kybic, C. , and C. , Needle localization methods in 3d ultrasound data, Proc. of International Congress on Ultrasonics, p.60, 2009.

F. Veronesi, C. Corsi, E. G. Caiani, and C. Lamberti, Nearly automated left ventricular long axis tracking on real time three-dimensional echocardiographic data, Computers in Cardiology, 2005, pp.5-8, 2005.
DOI : 10.1109/CIC.2005.1588018

S. Vijayan, S. Klein, E. F. Hofstad, F. Lindseth, B. Ystgaard et al., Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver, 2013 IEEE 10th International Symposium on Biomedical Imaging, pp.792-795, 2013.
DOI : 10.1109/ISBI.2013.6556594

Z. Wei, M. Ding, D. Downey, and A. Fenster, 3D TRUS Guided Robot Assisted Prostate Brachytherapy, Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.17-24, 2005.
DOI : 10.1007/11566489_3

W. Wein, S. Brunke, A. Khamene, M. R. Callstrom, and N. Navab, Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention, Medical Image Analysis, vol.12, issue.5, pp.577-585, 2008.
DOI : 10.1016/j.media.2008.06.006

W. Wein, J. Cheng, and A. Khamene, Ultrasound based respiratory motion compensation in the abdomen, Proc. of MICCAI Worshop on Image Guidance and Computer Assistance for Soft tissue Interventions, p.294, 2008.

W. Wein, O. Kutter, A. Aichert, D. Zikic, A. Kamen et al., Automatic non-linear mapping of pre-procedure CT volumes to 3D ultrasound, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1225-1228, 2010.
DOI : 10.1109/ISBI.2010.5490216

D. Xiao, W. S. Ng, C. B. Tsang, and U. R. Abeyratne, A region and gradient based active contour model and its application in boundary tracking on anal canal ultrasound images, Pattern Recognition, vol.40, issue.12, pp.403522-3539, 2007.
DOI : 10.1016/j.patcog.2007.03.024

F. Yeung, S. F. Levinson, D. Fu, P. , and K. J. , Feature-adaptive motion tracking of ultrasound image sequences using a deformable mesh, IEEE Transaction on Medical Imaging, issue.6, pp.17945-956, 1998.

Y. Hu, T. J. Carter, H. U. Ahmed, M. Emberton, C. Allen et al., Modelling Prostate Motion for Data Fusion During Image-Guided Interventions, IEEE Transactions on Medical Imaging, issue.11, pp.301887-1900, 2011.

P. A. Yushkevich, J. Piven, H. C. Hazlett, R. G. Smith, S. Ho et al., User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability, NeuroImage, vol.31, issue.3, pp.311116-1128, 2006.
DOI : 10.1016/j.neuroimage.2006.01.015

X. Zhang, M. Günther, and A. Bongers, Real-Time Organ Tracking in Ultrasound Imaging Using Active Contours and Conditional Density Propagation, Proc. of International Conference on Medical Imaging and Augmented Reality, pp.286-294, 2010.
DOI : 10.1007/978-3-642-15699-1_30

L. Royer, A. Krupa, G. Dardenne, A. Le-bras, E. Marchand et al., Real-time Target Tracking of Soft Tissues in 3D Ultrasound Images Based on Robust Visual Information and Mechanical Simulation Medical Image Analysis, accepted, available online A.2 International Conferences Real-time tracking of deformable target in 3D ultrasound images Tracking of Non-rigid Targets in 3D US Images: Results on CLUST 2015, Appendix A Publications and patents A.1 Scientific journal Proceedings of IEEE International Conference on Robotics and Automation, ICRA'15 Proceedings of MICCAI 2015 Challenge on Liver Ultrasound Tracking Marchal, A. Le Bras, G. Dardenne, A. Krupa. Tracking of Deformable Target in 2D Ultrasound Images Proceedings of SPIE Medical Imaging Conference, 2015.

L. Royer, M. Marchal, A. Le-bras, G. Dardenne, and A. Krupa, Interactive Tracking of Soft Tissues in 2D Ultrasound Images, Proceedings of SURGETICA, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01080676

L. Royer, M. Babel, and A. Krupa, Non-rigid target tracking in 2D ultrasound images using hierarchical grid interpolation, Proceedings of SPIE Medical Imaging Conference, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00933688