Segmentation of intravascular ultrasound images: a knowledge-based approach.

Segmentation of intravascular ultrasound images: a knowledge-based approach. Research Abstract Details 

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Segmentation of intravascular ultrasound images: a knowledge-based approach. Abstract Text:

M Sonka,X Zhang,M Siebes,M S Bissing,S C Dejong,S M Collins,C R McKay,

Intravascular ultrasound imaging of coronary arteries provides important information about coronary lumen, wall, and plaque characteristics. Quantitative studies of coronary atherosclerosis using intravascular ultrasound and manual identification of wall and plaque borders are limited by the need for observers with substantial experience and the tedious nature of manual border detection. We have developed a method for segmentation of intravascular ultrasound images that identifies the internal and external elastic laminae and the plaque-lumen interface. The border detection algorithm was evaluated in a set of 38 intravascular ultrasound images acquired from fresh cadaveric hearts using a 30 MHz imaging catheter. To assess the performance of our border detection method we compared five quantitative measures of arterial anatomy derived from computer-detected borders with measures derived from borders manually defined by expert observers. Computer-detected and observer-defined lumen areas correlated very well (r=0.96, y=1.02x+0.52), as did plaque areas (r=0.95, y=1.07x-0.48), and percent area stenosis (r=0.93, y=0.99x-1.34.) Computer-derived segmental plaque thickness measurements were highly accurate. Our knowledge-based intravascular ultrasound segmentation method shows substantial promise for the quantitative analysis of in vivo intravascular ultrasound image data.

Segmentation of intravascular ultrasound images: a knowledge-based approach. Publishing Authors By Initials

M Sonka,X Zhang,M Siebes,MS Bissing,SC Dejong,SM Collins,CR McKay,

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Segmentation of intravascular ultrasound images: a knowledge-based approach. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: IEEE transactions on medical imaging

VOLUME: 14

Page Numbers: 719-32

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ISSN: 0278-0062

DAY: 24

MONTH: 01

YEAR: 1995

Segmentation of intravascular ultrasound images: a knowledge-based approach. Information

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LANGUAGE: eng

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Grant and Affiliation Information for Segmentation of intravascular ultrasound images: a knowledge-based approach.

AFFILIATION: Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA.

Country: United States

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MEDLINETA: IEEE Trans Med Imaging

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