S. Belongie, Shape matching and object recognition using shape contexts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.4, pp.509-522, 2002.
DOI : 10.1109/34.993558

A. Bhattacharyya, On a measure of divergence between two statistical populations defined by their probability distribution, Bulletin of the Calcutta Math. Soc, vol.35, pp.99-110, 1943.

H. A. Bogers, Contrast-enhanced three-dimensional power doppler angiography of the human prostate: correlation with biopsy outcome, Urology, vol.54, issue.1, pp.97-104, 1999.
DOI : 10.1016/S0090-4295(99)00040-0

C. Domokos, Nonlinear Shape Registration without Correspondences, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.5, pp.943-958, 2012.
DOI : 10.1109/TPAMI.2011.200

N. Geva, Parametric modeling and linear estimation of elastic deformations, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1301-1304, 2011.
DOI : 10.1109/ICASSP.2011.5946650

S. Ghose, Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation, MICCAI-PCI, pp.35-46, 2011.
DOI : 10.1109/TMI.2005.862744

URL : https://hal.archives-ouvertes.fr/hal-00681463

J. Mitra, A Non-Linear Diffeomorphic Framework for Prostate Multimodal Registration, 2011 International Conference on Digital Image Computing: Techniques and Applications, pp.31-36, 2011.
DOI : 10.1109/DICTA.2011.14

URL : https://hal.archives-ouvertes.fr/hal-00682064

A. Y. Ng, On spectral clustering: Analysis and an algorithm, Adv. in Neural Info. Proc. Sys, pp.849-856, 2001.

S. Xu, Real-time MRI-TRUS fusion for guidance of targeted prostate biopsies, Computer Aided Surgery, vol.13, issue.5, pp.255-264, 2008.
DOI : 10.1007/978-3-540-75759-7_4