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Three-Dimensional Image Registration using a Locally Weighted-3D Distance Map  

Lee, Ho (서울대학교 전기컴퓨터공학부)
Hong, Helen (서울대학교 컴퓨터공학부)
Shin, Yeong-Gil (서울대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.7, 2004 , pp. 939-948 More about this Journal
Abstract
In this paper. we Propose a robust and fast image registration technique for motion correction in brain CT-CT angiography obtained from same patient to be taken at different time. First, the feature points of two images are respectively extracted by 3D edge detection technique, and they are converted to locally weighted 3D distance map in reference image. Second, we search the optimal location whore the cross-correlation of two edges is maximized while floating image is transformed rigidly to reference image. This optimal location is determined when the maximum value of cross-correlation does't change any more and iterates over constant number. Finally, two images are registered at optimal location by transforming floating image. In the experiment, we evaluate an accuracy and robustness using artificial image and give a visual inspection using clinical brain CT-CT angiography dataset. Our proposed method shows that two images can be registered at optimal location without converging at local maximum location robustly and rapidly by using locally weighted 3D distance map, even though we use a few number of feature points in those images.
Keywords
Medical imaging; Image registration; Distance map; Rigid transformation;
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Times Cited By KSCI : 1  (Citation Analysis)
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