title: Cardiac image segmentation for contrast agent videodensitometry.
abstract: Indicator dilution techniques are widely used in the intensive care unit and operating room for cardiac parameter measurements. However, the invasiveness of current techniques represents a limitation for their clinical use. The development of stable ultrasound contrast agents allows new applications of the indicator dilution method. Ultrasound contrast agent dilutions permit an echographic noninvasive measurement of cardiac output, ejection fraction, and blood volumes. The indicator dilution curves are measured by videodensitometry of specific regions of interest and processed for the cardiac parameter assessment. Therefore, the major indicator dilution imaging issue is the detection of proper contrast videodensitometry regions that maximize the signal-to-noise ratio of the measured indicator dilution curves. This paper presents an automatic contour detection algorithm for indicator dilution videodensitometry. The algorithm consists of a radial filter combined with an outlier correction. It maximizes the region of interest by excluding cardiac structures that act as interference to the videodensitometric analysis. It is fast, projection independent, and allows the simultaneous detection of multiple contours in real time. The system is compared to manual contour definition on both echographic and magnetic resonance images.
authors.affiliation: Eindhoven University of Technology, Eindhoven 5641 GP, The Netherlands. m.mischi@tue.nl
authors.forename: Massimo
authors.initials: M
authors.lastname: Mischi
authors.forename: Antonius A C M
authors.initials: AA
authors.lastname: Kalker
authors.forename: Hendrikus H M
authors.initials: HH
authors.lastname: Korsten
mesh_terms: D000465:Algorithms; D003720:Densitometry / Q000379:methods*; D004395:Dye Dilution Technique; D004452:Echocardiography / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014741:Video Recording / Q000379:methods*