title: Automatic detection of calcified coronary plaques in computed tomography data sets.
abstract: The detection of calcified plaques is an essential step in the assessment of coronary heart diseases. However, manual plaque segmentation is subjected to intra- and inter-observer variability. We present a novel framework for the automatic detection of calcified coronary plaques in Computed Tomography images. In contrast to the state-of-the-art, both the native and the angio data sets are included to gain additional information about each plaque for its detection and subsequent assessment. The framework was successfully tested on 127 patients where 85.5% of the calcified and 96% of the obstructive plaques have been detected.
authors.affiliation: Computer Vision Laboratory, ETH Zurich, Switzerland. saur@vision.ee.ethz.ch
authors.forename: Stefan C
authors.initials: SC
authors.lastname: Saur
authors.forename: Hatem
authors.initials: H
authors.lastname: Alkadhi
authors.forename: Lotus
authors.initials: L
authors.lastname: Desbiolles
authors.forename: Gábor
authors.initials: G
authors.lastname: Székely
authors.forename: Philippe C
authors.initials: PC
authors.lastname: Cattin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D002114:Calcinosis / Q000000981:diagnostic imaging*; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*