title: Localizing calcifications in cardiac CT data sets using a new vessel segmentation approach.
abstract: The new generation of multislice computed tomography (CT) scanners allows for the acquisition of high-resolution images of the heart. Based on that image data, the heart can be analyzed in a noninvasive way-improving the diagnosis of cardiovascular malfunctions on one hand, and the planning of an eventually necessary intervention on the other. One important parameter for the evaluation of the severity of a coronary artery disease is the number and localization of calcifications (hard plaques). This work presents a method for localizing these calcifications by employing a newly developed vessel segmentation approach. This extraction technique has been developed for, and tested with, contrast-enhanced CT data sets of the heart. The algorithm provides enough information to compute the vessel diameter along the extracted segment. An approach for automatically detecting calcified regions that combines diameter information and gray value analysis is presented. In addition, specially adapted methods for the visualization of these analysis results are described.
authors.affiliation: Department of Cognitive Computing & Medical Imaging, Darmstadt, Germany. stefan.wesarg@igd.fraunhofer.de
authors.forename: Stefan
authors.initials: S
authors.lastname: Wesarg
authors.forename: M Fawad
authors.initials: MF
authors.lastname: Khan
authors.forename: Evelyn A
authors.initials: EA
authors.lastname: Firle
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002114:Calcinosis / Q000150:complications / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D009202:Cardiomyopathies / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000209:etiology / Q000473:pathology*; D003287:Contrast Media / Q000008:administration & dosage; D003324:Coronary Artery Disease / Q000150:complications / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology*; D005189:False Positive Reactions; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015588:Observer Variation; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D014796:Visual Perception
chemical_list: D003287:Contrast Media