Y. Ng, V. Mann, S. Rahbaran, J. Lewsey, and K. Gulabivala, Outcome of primary root canal treatment: Systematic review of the literature-Part 1. Effects of study characteristics on probability of success, Int. Endodontic J, vol.40, issue.12, pp.921-939, 2007.

H. M. Eriksen, L. Kirkevang, and K. Petersson, Endodontic epidemiology and treatment outcome: General considerations, Endodontic Topics, vol.2, issue.1, pp.1-9, 2002.

O. A. Peters, Current challenges and concepts in the preparation of root canal systems: A review, J. Endodontics, vol.30, issue.8, pp.559-567, 2004.

K. Horner and S. Panel, European Commission: Directorate-General for Energy, 2012, the Seventh Framework Programme of the European Atomic Energy Community (Euratom) for Nuclear Research and Training Activities, Accessed: Jul. 15, 2007.

F. C. Setzer, N. Hinckley, M. R. Kohli, and B. Karabucak, A survey of cone-beam computed tomographic use among endodontic practitioners in the united states, J. Endodontics, vol.43, issue.5, pp.699-704, 2017.

J. Martos, G. H. Tatsch, A. C. Tatsch, L. F. Silveira, and C. M. Ferrer-luque, Anatomical evaluation of the root canal diameter and root thickness on the apical third of mesial roots of molars, Anatomical Sci. Int, vol.86, issue.3, pp.146-150, 2011.

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, Fast and robust multiframe super resolution, IEEE Trans. Image Process, vol.13, issue.10, pp.1327-1344, 2004.

H. Yin, S. Li, and L. Fang, Simultaneous image fusion and superresolution using sparse representation, Inf. Fusion, vol.14, issue.3, pp.229-240, 2013.

K. I. Kim and Y. Kwon, Single-image super-resolution using sparse regression and natural image prior, IEEE Trans. Pattern Anal. Mach. Intell, vol.32, issue.6, pp.1127-1133, 2010.

A. Toma, L. Denis, B. Sixou, J. B. Pialat, and F. Peyrin, Total variation super-resolution for 3D trabecular bone micro-structure segmentation, Proc. 22nd Eur. Signal Process. Conf. (EUSIPCO), pp.2220-2224, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01076159

F. Shi, J. Cheng, L. Wang, P. Yap, and D. Shen, LRTV: MR image super-resolution with low-rank and total variation regularizations, IEEE Trans. Med. Imag, vol.34, issue.12, pp.2459-2466, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01154770

W. Zhang, H. Zhang, L. Wang, A. Cai, L. Li et al., Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame, Nucl. Instrum. Methods Phys. Res. A, Accel. Spectrom. Detect. Assoc. Equip, vol.880, pp.107-117, 2018.

J. V. Manjón, P. Coupé, A. Buades, V. Fonov, D. L. Collins et al., Non-local MRI upsampling, Med. Image Anal, vol.14, issue.6, pp.784-792, 2010.

O. Oktay, Multi-input cardiac image super-resolution using convolutional neural networks, Proc. 19th MICCAI Int. Conf, pp.246-254, 2016.

S. Cengiz, M. D. Valdes-hernandez, and E. Ozturk-isik, Super resolution convolutional neural networks for increasing spatial resolution of 1 h magnetic resonance spectroscopic imaging, Proc. 21st MIUA Annu. Conf, pp.641-650, 2017.

Y. Zhang and M. An, Deep learning-and transfer learningbased super resolution reconstruction from single medical image, J. Healthcare Eng, vol.2017, issue.5859727, 2017.

J. Hatvani, A. Horvath, J. Michetti, A. Basarab, D. Kouamé et al., Deep learning-based super-resolution applied to dental computed tomography, IEEE Trans. Radiat. Plasma Med. Sci

C. I. Kanatsoulis, X. Fu, N. D. Sidiropoulos, and W. Ma, Hyperspectral super-resolution: A coupled tensor factorization approach, 2018.

T. G. Kolda and B. W. Bader, Tensor decompositions and applications, SIAM Rev, vol.51, issue.3, pp.455-500, 2009.

L. Chiantini and G. Ottaviani, On generic identifiability of 3-tensors of small rank, SIAM J. Matrix Anal. Appl, vol.33, issue.3, pp.1018-1037, 2012.

J. H. Elder and S. W. Zucker, Local scale control for edge detection and blur estimation, IEEE Trans. Pattern Anal. Mach. Intell, vol.20, issue.7, pp.699-716, 1998.

M. Fuhry and L. Reichel, A new Tikhonov regularization method, Numer. Algorithms, vol.59, issue.3, pp.433-445, 2012.

N. Vervliet, O. Debals, L. Sorber, M. V. Barel, and L. De-lathauwer, , 2016.

J. Michetti, A. Basarab, F. Diemer, and D. Kouame, Comparison of an adaptive local thresholding method on CBCT and ?CT endodontic images, Phys. Med. Biol, vol.63, issue.1, p.15020, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01790397

L. R. Dice, Measures of the amount of ecologic association between species, Ecology, vol.26, issue.3, pp.297-302, 1945.

, MeVis Medical Solutions AG, 2017.

F. Shi, J. Cheng, L. Wang, P. Yap, and D. Shen, Low-rank total variation for image super-resolution, Proc. 16th Int. Conf. Med. Image Comput. Assist. Interv. (MICCAI), pp.155-162, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01485563