Assessment of vessel complexity in knowledge-based coronary border detection

The incorporation of knowledge about global image characteristics and coronary anatomy can improve the accuracy ad robustness of automated identification of coronary borders from cineangiograms. Ideally, the importance assigned by the analysis method to such knowledge versus that assigned to local i...

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Published inIEEE, PISCATAWAY, NJ, (USA). no. 00-601. 1993 no. 601; pp. 598 - 599
Main Authors Tadikonda, S.K., Sonka, M., Xiangmin Zhang, Collins, S.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1993
Subjects
Anatomy
Cities and towns
Geometry
Heart
Image analysis
Image edge detection
Image segmentation
Medical treatment
Radiology
Robustness
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Summary:The incorporation of knowledge about global image characteristics and coronary anatomy can improve the accuracy ad robustness of automated identification of coronary borders from cineangiograms. Ideally, the importance assigned by the analysis method to such knowledge versus that assigned to local image gradient magnitudes should depend upon the local complexity of the vessel image. We report here the design and evaluation of an automated method for assessing vessel complexity.
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ISBN:0780313771
9780780313774
DOI:10.1109/IEMBS.1993.978709