TAG AND CONTOUR-DETECTION IN TAGGED MR-IMAGES OF THE LEFT-VENTRICLE

Tracking magnetic resonance tags in myocardial tissue promises to be a n effective tool for the assessment Of myocardial motion. In this pape r we describe a hierarchy of image processing steps which rapidly dete cts both the contours of the myocardial boundaries of the left ventric le and the tags within the myocardium. The method works on both short axis and long axis images containing radial and parallel tag patterns, respectively. Left ventricular boundaries are detected by first remov ing the tap using morphological closing and then selecting candidate e dge points. The best inner and outer boundaries are found using a dyna mic program that minimizes a nonlinear combination of several local co st functions. Tags are tracked by matching a template of their expecte d profile using a least squares estimate. Since blood pooling, contigu ous and adjacent tissue, and motion artifacts sometimes cause detectio n errors, a graphical user interface was developed to allow user corre ction of anomalous points. We present results on several tagged images of a human. A fully automated run generally finds the endocardial bou ndary and the tag lines extremely well, requiring very little manual c orrection. The epicardial boundary sometimes requires more interventio n to obtain an acceptable result. These methods are currently being us ed in the analysis of cardiac strain and as a basis for the analysis o f alternate tag geometries.