LVEDGE: A Knowledge-Based Heuristic Program For Border Finding Of The Left Ventricular Cavity In Cardiac Digital X-Ray Images

Traditional edge-detection methods have involved grey-level thresholding and pixel neighborhood operations, as well as tracking algorithms. These purely mathematical aroaches have a tendency to generate many extra edges not relevant to the desired edge and are often fooled by artifacts such as catheters or rib boundaries. LVEDGE utilizes several techniques from artificial intelligence to deal with these difficulties. It has a user trainable knowledge-base to constrain the search to an expected left ventricular (LV) shape. A structure likelihood matrix is created based onprobabilities that pixels are on the actual edge. This matrix is then dynamically searched incorporating both local and global information to generate the most likely continuous single edge of the ventricle. The program has been run on digital LV images (some quite poor) and has compared favorably to human generated edges. The generated edges can be input to standard cardiac function analysis software (ejection fraction, regional wall motion, etc.)