Methods, systems, and computer readable media for real-time 2D/3D deformable registration using metric learning are disclosed. According to one aspect, a method for real-time 2D/3D deformable registration using metric learning includes creating a catalogue of simulated 2D projection images based on a reference 3D image and a shape space of 3D deformations, where each entry in the catalogue is created by: applying to the reference 3D image a set of deformation parameters from the shape space of deformations simulating a 2D projection of the result associating the simulated 2D projection image with the deformation parameters used to create the simulated 2D projection image and storing the simulated 2D projection image and associated deformation parameters in the catalogue. The method also includes receiving a 2D image, and, in response to receiving the 2D image: calculating a value of distance between the received 2D image and a simulated 2D projection image for each of the simulated 2D projection images in the catalogue using the calculated distances to calculate weighting factors to be applied to the deformation parameters of each of the simulated 2D projection images in the catalogue and calculating deformation parameters for the received 2D image based on the weighted deformation parameters in the catalogue. The calculated deformation parameters are then used to deform a 3D volume of interest to produce a 3D volume that represents the 3D layout of the tissue at the time that the received 2D image was acquired.Linvention concerne des procédés, des systèmes et des supports lisibles par ordinateur pour alignement déformable en 2D/3D en temps réel utilisant un apprentissage de mesures. Selon un aspect, un procédé pour alignement déformable en 2D/3D en temps réel utilisant un apprentissage de mesures comprend la création dun catalogue dimages de projection 2D sur la base dune image 3D de référence et dun espace de forme de déformations 3D, où chaque entrée dans le cata
