Maximum intensity projection (MIP) studies of CT angiography (CTA) images are a widely used tool for artery and vein visualization especially in the brain. Due to their high CT intensity bone structures lead to visualization artifacts in MIP studies, therefore they have to be removed to get an undistorted view of the vessel structures. Often this removal is possible by a rigid registration step...

This lecture continues the subject of point based rigid registration. An important aspect of the algorithms previously presented was the assumption that the pairing between point coordinates in the two coordinate systems is known. In this lecture we present an algorithm which will not require this assumption and furthermore does not require a full pairing between data sets. Problem Definition G...

Assume that only partial knowledge about a non-rigid registration is given: certain points, curves or surfaces in one 3D image are known to map to certain points, curves or surfaces in another 3D image. In trying to identify the non-rigid displacement field, we face a generalized aperture problem since along the curves and surfaces, point correspondences are not given. We will advocate the view...

This paper addresses the issue of matching rigid 3D object points with 2D image points through point registration based on maximum likelihood principle in computer simulated images. Perspective projection is necessary when transforming 3D coordinate into 2D. The problem then recasts into a missing data framework where unknown correspondences are handled via mixture models. Adopting the Expectat...

A deformable registration approach for medical images of same dimensionality is proposed. The popular free-form deformations (FFD) setting is utilized to characterize deformations based on a grid of control points. B-splines serve the purpose of interpolating the dense deformation field from a given control point configuration. The central idea is to combine the FFD method with well-understood ...

We present a generic method for assessing the quality of non-rigid registration (NRR), that does not require ground truth, but rather depends solely on the registered images. We consider the case where NRR is applied to a set of images, providing a dense correspondence between images. Given this correspondence, it is possible to build a generative statistical model of appearance variation for t...

Advanced imaging techniques have been widely used to study the anatomical structure and functional metabolism in medical and clinical applications. Images are acquired from a variety of scanners (CT/MR/PET/SPECT/Ultrasound), which provide physicians with complementary information to diagnose and detect specific regions of a patient. However, due to the different modalities and imaging orientati...

We have developed a new mutual information-based registration method for matching unlabeled point features. In contrast to earlier mutual information-based registration methods, which estimate the mutual information using image intensity information, our approach uses the point feature location information. A novel aspect of our approach is the emergence of correspondence (between the two sets ...

Image registration is the fundamental task used to match two or more partially overlapping images taken at different times, from different sensors, or from different viewpoints. It is a technique useful in integrating information from different sources. Image registration techniques can be based upon image gray-scale or image features. Feature based registration gives a coarse result. Thus, usi...