Left ventricular border recognition using a dynamic search algorithm.
Initial results obtained with a simple, fully automated algorithm for detection of left ventricular boundaries are presented. The strength of this approach is the use of dynamic programming search techniques, which allow determination of local border points to be influenced by the entire global border location. The relative contributions of mask mode subtraction and the dynamic search technique are evaluated with respect to accurate border definition. These computer-determined ventricular borders are compared with hand-traced borders on subtracted and unsubtracted images. The modular dynamic search algorithm is shown to perform better than previously described algorithms, which generally require operator interaction. It is also shown that for both manual and automated techniques, ventricular borders derived from subtracted images may be significantly different from borders derived from nonsubtracted images.
D000790:Angiocardiography; D002932:Cineangiography; D003201:Computers; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D011877:Radionuclide Imaging; D013382:Subtraction Technique