Abstract: 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 catalog of simulated 2D projection images based on a reference 3D image and a shape space of 3D deformations, where each entry in the catalog 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 catalog.

Abstract: 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.

Abstract: Methods, systems, and computer readable media for mapping a model of an object comprising an anatomical structure in a planning image and an intervention target region within it to intervention-guiding image data are disclosed. According to one method, an initial medial representation object model (m-rep) of an object comprising an anatomical structure is created based on image data of at least a first instance of the object. A patient-specific m-rep is created by deforming the initial m-rep based on planning image data of at least a second instance of the object, wherein the at least second instance of the object is associated with the patient. An intervention target region within the m-rep is identified in an image registered with the planning image. The patient-specific m-rep is correlated to the intervention-guiding image data of the at least second instance of the object, deformed from the planning image.

Abstract: Methods, systems, and computer readable media for mapping a model of an object comprising an anatomical structure in a planning image and an intervention target region within it to intervention-guiding image data are disclosed. According to one method, an initial medial representation object model (m-rep) of an object comprising an anatomical structure is created based on image data of at least a first instance of the object. A patient-specific m-rep is created by deforming the initial m-rep based on planning image data of at least a second instance of the object, wherein the at least second instance of the object is associated with the patient. An intervention target region within the m-rep is identified in an image registered with the planning image. The patient-specific m-rep is correlated to the intervention-guiding image data of the at least second instance of the object, deformed from the planning image.