title: A general technique for automatic left ventricle boundary validation: relation between gray scale cardioangiograms and observed boundary errors.
abstract: This article presents an automatic left ventricle boundary validation technique using the gray scale cardioangiograms, the observed boundary errors, and the left ventricle boundaries from any source that needs to be validated. This validation technique is based on the gray scale information near the boundary of the left ventricle in the cardioangiograms. Using a mutually exclusive window of fixed size, which is centered on the left ventricle boundary vertex and along the left ventricle contour, we compute a difference in contrast value for areas of the window both inside and outside the left ventricle region. These contrast values then are regressed against the observed boundary errors. The observed boundary errors are computed using the polyline distance measure, by comparing two sets of boundaries: boundaries estimated from any boundary estimation algorithm, and the original ground truth boundaries as traced by the cardiologist. We performed our experiments on a database of 245 patient studies, each having two frames: end-diastole (ED) and end-systole (ES). The mean boundary error before running the validation system was 4.4 mm. Using our boundary validation system, by rejecting 5% to 10% of the patient studies, the validation system results in an error of 4.0 mm for the cross-validation case and 3.85 mm for the ideal case. We show the reliability curves of our validation system by computing the probability of false alarm, probability of mis-detection, and mean predicted errors when a total of n patients are rejected from the database of 245 studies.
authors.affiliation: Intelligent Systems Laboratory, University of Washington, Seattle 98195, USA.
authors.forename: J S
authors.initials: JS
authors.lastname: Suri
authors.forename: R M
authors.initials: RM
authors.lastname: Haralick
authors.forename: F H
authors.initials: FH
authors.lastname: Sheehan
mesh_terms: D000465:Algorithms; D000790:Angiocardiography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D012815:Signal Processing, Computer-Assisted