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Proceedings Paper

Motion correction for CT angiography quality enhancement
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Paper Abstract

In this paper, we present a novel technique of improving vessel visualization quality by removing motion artifacts in digital subtraction brain CT angiography. The proposed methods based on the three key ideas as follows. First, the method involves the automatic selection of a set of feature points by using a 3D edge detection technique based on image gradient of mask and contrast volume. Second, locally weighted-3D distance map is generated to derive to robust convergence on the optimum value. Third, the similarity measure between extracted feature points is evaluated repeatedly by selective cross-correlation. The proposed method has been successfully applied to pre- and post-contrast CT angiography based on brain dataset for global and spatial motion correction. The feature point selection, introducing local processing on areas of interest consisting of voxels belonging to object boundary only, are very fast compared to all traditional algorithms where entire volume are searched. Since the registration estimates similarity measures between feature points and derive to robust convergence on the optimum value by the locally weighted-3D distance map, it offers an accelerated technique to accurately visualize vessels of the brain.

Paper Details

Date Published: 12 May 2004
PDF: 10 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.535673
Show Author Affiliations
Helen Hong, Seoul National Univ. (South Korea)
Ho Lee, Seoul National Univ. (South Korea)
Yeong-Gil Shin, Seoul National Univ. (South Korea)


Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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