A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spline-Based Image Registration
International Journal of Computer Vision
Degraded Image Analysis: An Invariant Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Basic Concepts of Digital Subtraction Angiography
Basic Concepts of Digital Subtraction Angiography
Image Registration for Digital Subtraction Angiography
International Journal of Computer Vision
Multiresolution Image Registration in Digital X-Ray Angiography with Intensity Variation Modeling
Journal of Medical Systems
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A serious problem encountered in digital subtraction angiography (DSA) is the presence of artifacts due to patient motion. The resulting artifacts which arise from the misalignment of successive images in the sequence frequently reduce the diagnostic value of the images and lead to misdiagnosis or rejection of a DSA image sequence. A possible solution is the use of image registration techniques. In this paper, an invariant approach to elastic registration based on local similarity detection according to a combined invariants-based similarity measure, in which the images are locally registered and elastically interpolated, is presented. To improve the registration, a 3-D space time motion-detection technique for extracting movement point pairs in a sequence of X-ray images is proposed. It is shown that such a technique is very efficient to correct for both global and local motion artifacts. The proposed algorithm for this technique has been successfully applied to register several clinical data sets including coronary applications. The results show that a fast and accurate image registration is achieved and that the algorithm is robust, which makes it clinically applicable.