Shape-driven segmentation of the arterial wall in intravascular ultrasound images

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Ünal, Gözde and Bucher, Susann and Carlier, Stephane and Slabaugh, Greg and Fang, Tong and Tanaka, Kaoru (2008) Shape-driven segmentation of the arterial wall in intravascular ultrasound images. IEEE Transactions on Information Technology in Biomedicine, 12 (3). pp. 335-347. ISSN 1089-7771 (Print) 1558-0032 (Online)

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Abstract

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a non-parametric probability density based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach.
Item Type: Article
Uncontrolled Keywords: Arterial wall segmentation arterial wall segmentation calcification detection intensity prior, intravascular ultrasound, intravascular ultrasound (IVUS), lumen segmentation, media adventitia segmentation, model-based segmentation, shape prior, side branch detection
Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Gözde Ünal
Date Deposited: 08 Jun 2008 18:00
Last Modified: 26 Apr 2022 08:19
URI: https://research.sabanciuniv.edu/id/eprint/8586

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