A review of coronary vessel segmentation algorithms
Author(s) -
MaryamTaghizadeh Dehkordi,
Saeed Sadri,
Alimohamad Doosthoseini
Publication year - 2011
Publication title -
journal of medical signals and sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.337
H-Index - 21
ISSN - 2228-7477
DOI - 10.4103/2228-7477.83519
Subject(s) - segmentation , coronary arteries , coronary vessel , coronary angiography , coronary artery disease , gold standard (test) , coronary angiogram , computer science , medicine , artery , coronary heart disease , radiology , tree (set theory) , cardiology , artificial intelligence , computer vision , mathematics , myocardial infarction , mathematical analysis
Coronary heart disease has been one of the main threats to human health. Coronary angiography is taken as the gold standard; for the assessment of coronary artery disease. However, sometimes, the images are difficult to visually interpret because of the crossing and overlapping of vessels in the angiogram. Vessel extraction from X-ray angiograms has been a challenging problem for several years. There are several problems in the extraction of vessels, including: weak contrast between the coronary arteries and the background, unknown and easily deformable shape of the vessel tree, and strong overlapping shadows of the bones. In this article we investigate the coronary vessel extraction and enhancement techniques, and present capabilities of the most important algorithms concerning coronary vessel segmentation.
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