Medical imaging can be performed with a variety of imaging modalities, e.g., computed tomography (CT), magnetic resonance (MR), single photon emission computed tomography (SPECT), positron emission tomography (PET), ultrasonographic (US), etc. Each type of imaging involves measuring some property or function of the patient, and forming images (e.g., 2D, 3D, or 4D images) that can be used by a trained expert to extract relevant medical information. The amalgamation of information from various modalities holds the promise of a synergistic effect. Overlaying images obtained from two different modalities and viewing them together offers additional benefits for analyzing the images for medical diagnosis. The overlaying of two images from two different modalities involves registering the two images so they are properly aligned.
The process of image registration involves relating a property or function measured with an imaging modality at a spatio-temporal location to a common coordinate system. Such a common coordinate system could either be defined by data of another imaging modality, by the system's reference coordinates, or arbitrarily by the user. Registration is of interest in multimodality imaging for applications in diagnostic imaging and image guided therapy planning, execution, and monitoring. For example, consider a scenario in which a first image obtained via CT shows a patient's bones in the rib cage, and a second image obtained via magnetic resonance (MR) shows the patient's heart. If the images can be referenced to a common coordinate system, then it is possible to manipulate one of the images so that an overlay or composite image reveals the bones as well as the heart.
Registration methods essentially involve determining transformations for achieving a best fit for an image of one modality, the object image, onto an image of another modality, the reference or target image. As such, an optimization problem is typically set up and solved, e.g., a minimization of a distance measured between the target image and the object image, under one or more constraints. Typically, the target image is fixed, and the object image is varied subject to the constraints for the optimization. Image registration is described in greater detail in Maintz et al., “A Survey of Medical Imaging Registration,” Medical Image Analysis, 1998, v2, the entirety of which is hereby incorporated by reference herein.
In rigid registrations the assumption is made that the objects or components present in the images (e.g., in the object image) are ideal solids behaving as rigid bodies, such that only congruent rotation and translation operations are allowed. This imposes the most stringent constraints on the minimization, and such constraints are often needed to even arrive at a reasonable solution, as the data are often not only noisy, but also represent different material properties or functions probed by the different modalities. A drawback of using only rigid registration is that while it may yield good results for bones, the results may be poor for soft tissues that do not physically behave as rigid bodies.
In order to accomplish registration of soft tissue images, non-rigid registration methods allowing for elastic deformation have previously been developed. By incorporating elastic deformation, motions or transformations of objects are allowed as part of the optimization process. These motions or transformations of objects include not only rotations and translations, but also stretching, compression, and shearing. However, the existing non-rigid registration methods typically lead to undesirable artifacts such as elongated or otherwise distorted bones, rather than deformed soft tissues. Non-rigid deformable registration and deformable models are described in more detail in Bharatha et al., “Evaluation of three-dimensional finite element-based deformable registration of pre- and intra-operative prostate imaging,” Med. Phys. 28(12), 2001 and Metaxas, D. N., Physics-Based Deformable Models: Applications to Computer Vision, Graphics, and Medical Imaging, 1st edition, which references are hereby incorporated by reference herein in their entireties.