. Andres, H. Jörg, T. Kappes, U. Beier, F. A. Köthe et al., The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models, Computer Vision?ECCV 2012, pp.154-166, 2012.
DOI : 10.1007/978-3-642-33786-4_12

J. Besag, Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986.
DOI : 10.1016/0031-3203(83)90012-2

P. Baudin, D. Goodman, P. Kumar, N. Azzabou, G. Pierre et al., Discriminative Parameter Estimation for Random Walks Segmentation, Medical Image Computing and Computer-Assisted Intervention?MICCAI 2013, pp.219-226, 2013.
DOI : 10.1007/978-3-642-40760-4_28

URL : https://hal.archives-ouvertes.fr/hal-00856020

G. Adam, . Chandler, J. Richard, T. Pinder, J. A. Netsch et al., Correction of misaligned slices in multi-slice mr cardiac examinations by using slice-to-volume registration, Journal of Cardiovascular Magnetic Resonance2008, p.13, 2008.

[. Dalvi and R. Abugharbieh, Fast feature based multi slice to volume registration using phase congruency, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.5390-5393, 2008.
DOI : 10.1109/IEMBS.2008.4650433

P. Aydin-eresen, J. X. Li, and . Ji, Correlating 2d histological slice with 3d mri image volume using smart phone as an interactive tool for muscle study, 2014 36th Annual International Conference of the IEEE, pp.6418-6421, 2014.

B. Fei, L. Jeffrey, . Duerk, T. Daniel, . Boll et al., Slice-to-volume registration and its potential application to interventional mri-guided radio-frequency thermal ablation of prostate cancer, Medical Imaging IEEE Transactions on, vol.22, issue.4, pp.515-525, 2003.

[. Ferrante, V. Fecamp, and N. Paragios, Implicit planar and inplane deformable mapping in medical images through high order graphs, IEEE International Symposium on BIOMEDICAL IMAGING: From Nano to Macro (ISBI), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01130724

[. Ferrante, V. Fecamp, and N. Paragios, Slice-to-volume deformable registration: efficient one-shot consensus between plane selection and in-plane deformation, International Journal of Computer Assisted Radiology and Surgery, vol.14, issue.4, p.16, 2015.
DOI : 10.1007/s11548-015-1205-2

URL : https://hal.archives-ouvertes.fr/hal-01118871

[. Ferrante and N. Paragios, Non-rigid 2D-3D Medical Image Registration Using Markov Random Fields, Medical Image Computing and Computer- Assisted Intervention?MICCAI 2013, pp.163-170, 2013.
DOI : 10.1007/978-3-642-40760-4_21

URL : https://hal.archives-ouvertes.fr/hal-00855662

[. Fuerst, W. Wein, M. Muller, and N. Navab, Automatic ultrasound???MRI registration for neurosurgery using the 2D and 3D LC2 Metric, Special Issue on the 2013 Conference on Medical Image Computing and Computer Assisted Intervention, pp.1312-1319, 2014.
DOI : 10.1016/j.media.2014.04.008

P. S. Gill, S. Abolmaesumi, P. Vikal, G. Mousavi, and . Fichtinger, Intraoperative prostate tracking with slice-to-volume registration in mri, pp.154-158, 2008.

B. Glocker, N. Komodakis, N. Paragios, and N. Navab, Approximated Curvature Penalty in Non-rigid Registration Using Pairwise MRFs, Advances in Visual Computing, pp.1101-1109, 2009.
DOI : 10.1007/978-3-642-10331-5_102

N. Gkt-+-08-]-ben-glocker, G. Komodakis, N. Tziritas, N. Navab, and . Paragios, Dense image registration through MRFs and efficient linear programming???, Medical Image Analysis, vol.12, issue.6, pp.731-741, 2007.
DOI : 10.1016/j.media.2008.03.006

B. Glocker, A. Sotiras, N. Komodakis, and N. Paragios, Deformable Medical Image Registration: Setting the State of the Art with Discrete Methods, Annual Review of Biomedical Engineering, vol.13, issue.1, pp.219-244, 2011.
DOI : 10.1146/annurev-bioeng-071910-124649

URL : https://hal.archives-ouvertes.fr/hal-00858380

J. Huang, G. Moore, . Guiraudon, L. Douglas, D. Jones et al., Dynamic 2d ultrasound and 3d ct image registration of the beating heart, Medical Imaging IEEE Transactions on, issue.8, pp.281179-1189, 2009.

H. Jiang, S. Xue, M. Counsell, J. Anjari, M. Allsop et al., Diffusion tensor imaging (DTI) of the brain in moving subjects: Application to in-utero fetal and ex-utero studies, Magnetic Resonance in Medicine, vol.38, issue.Pt 1, pp.645-655, 2009.
DOI : 10.1002/mrm.22032

H. Jorg, B. Kappes, F. A. Andres, C. Hamprecht, S. Schnörr et al., A comparative study of modern inference techniques for discrete energy minimization problem, 2013.

B. Kim, J. L. Boes, H. Peyton, . Bland, L. Thomas et al., Motion correction in fmri via registration of individual slices into an anatomical volume, 1999.

R. Frank, . Kschischang, J. Brendan, H. Frey, and . Loeliger, Factor graphs and the sum-product algorithm. Information Theory, IEEE Transactions on, vol.47, issue.2, pp.498-519, 2001.

K. Klyl08-]-dongjin-kwon, D. Lee, S. U. Yun, and . Lee, Nonrigid image registration using dynamic higher-order mrf model, Computer Vision?ECCV 2008, pp.373-386, 2008.

I. Komodakis, N. Paragios, and G. Tziritas, Mrf energy minimization and beyond via dual decomposition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.33, issue.3, pp.531-552, 2011.
DOI : 10.1109/tpami.2010.108

URL : https://hal.archives-ouvertes.fr/hal-00856311

C. [. Kohli and . Rother, Higher-order models in computer vision, Image Processing and Analysis with Graphs, vol.1, p.2012

G. [. Komodakis, N. Tziritas, and . Paragios, Fast, Approximately Optimal Solutions for Single and Dynamic MRFs, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383095

[. Komodakis, B. Xiang, and N. Paragios, A Framework for Efficient Structured Max-Margin Learning of High-Order MRF Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, issue.7, 2015.
DOI : 10.1109/TPAMI.2014.2368990

URL : https://hal.archives-ouvertes.fr/hal-01245673

R. Liao, L. Zhang, and Y. Sun, Shun Miao, and Christophe Chefd'Hotel. A review of recent advances in registration techniques applied to minimally invasive therapy. Multimedia, IEEE Transactions on, vol.15, issue.5, pp.983-1000, 2013.

L. Mercier, R. F. , D. Maestro, K. Petrecca, D. Araujo et al., Online database of clinical MR and ultrasound images of brain tumors, Medical Physics, vol.11, issue.3, p.3253, 2012.
DOI : 10.1118/1.4709600

P. Markelj, D. Toma?evi?, B. Likar, and F. Pernu?, A review of 3d/2d registration methods for image-guided interventions. Medical image analysis, 2012.

J. Olesch, B. Beuthien, S. Heldmann, N. Papenberg, and B. Fischer, Fast intra-operative non-linear registration of 3D-CT to tracked, selected 2D-ultrasound slices, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, pp.79642-79642, 2011.
DOI : 10.1117/12.878105

N. Paragios and N. Komodakis, Discrete Visual Perception, 2014 22nd International Conference on Pattern Recognition, pp.18-25, 2014.
DOI : 10.1109/ICPR.2014.13

URL : https://hal.archives-ouvertes.fr/hal-01023406

[. Ramalingam, P. Kohli, K. Alahari, H. Philip, and . Torr, Exact inference in multi-label CRFs with higher order cliques, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587401

URL : https://hal.archives-ouvertes.fr/hal-01217304

. Daniel-rueckert, I. Luke, C. Sonoda, . Hayes, L. Derek et al., Nonrigid registration using free-form deformations: application to breast mr images, Medical Imaging IEEE Transactions on, issue.8, pp.18712-721, 1999.

[. 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

M. Seshamani, X. Fogtmann, . Cheng, C. Thomason, C. Gatenby et al., Cascaded slice to volume registration for moving fetal FMRI, 2013 IEEE 10th International Symposium on Biomedical Imaging, pp.796-799, 2013.
DOI : 10.1109/ISBI.2013.6556595

[. Estépar, C. F. Westin, and K. G. Vosburgh, Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures, International Journal of Computer Assisted Radiology and Surgery, vol.12, issue.5, pp.549-560, 2009.
DOI : 10.1007/s11548-009-0369-z

[. Shekhovtsov, I. Kovtun, and V. Hlavá?, Efficient MRF deformation model for non-rigid image matching, Computer Vision and Image Understanding, vol.112, issue.1, pp.91-99, 2008.
DOI : 10.1016/j.cviu.2008.06.006

Y. Sotiras, B. Ou, C. Glocker, N. Davatzikos, and . Paragios, Simultaneous Geometric - Iconic Registration, Medical Image Computing and Computer-Assisted Intervention?MICCAI 2010, pp.676-683
DOI : 10.1007/978-3-642-15745-5_83

URL : https://hal.archives-ouvertes.fr/hal-00856046

C. Wang, N. Komodakis, and N. Paragios, Markov Random Field modeling, inference & learning in computer vision & image understanding: A survey, Computer Vision and Image Understanding, vol.117, issue.11, pp.1610-1627, 2013.
DOI : 10.1016/j.cviu.2013.07.004

URL : https://hal.archives-ouvertes.fr/hal-00858390

H. Xu, A. Lasso, A. Fedorov, K. Tuncali, C. Tempany et al., Multi-slice-to-volume registration for MRI-guided transperineal prostate biopsy, International Journal of Computer Assisted Radiology and Surgery, vol.57, issue.6, pp.1-10, 2014.
DOI : 10.1007/s11548-014-1108-7

M. Yim, C. Wakid, S. Kirmizibayrak, J. Bielamowicz, and . Hahn, Registration of 3D CT Data to 2D Endoscopic Image using a Gradient Mutual Information based Viewpoint Matching for Image-Guided Medialization Laryngoplasty, Journal of Computing Science and Engineering, vol.4, issue.4, pp.368-387, 2010.
DOI : 10.5626/JCSE.2010.4.4.368

B. Zikic, O. Glocker, M. Kutter, N. Groher, A. Komodakis et al., Linear intensity-based image registration by Markov random fields and discrete optimization, Medical Image Analysis, vol.14, issue.4, pp.550-562, 2010.
DOI : 10.1016/j.media.2010.04.003

URL : https://hal.archives-ouvertes.fr/hal-00856077