Automatic Selection of Keyframes from Angiogram Videos

In this paper we address the problem of automatic selection of important vessel-depicting key frames within 2D angiography videos. Two different methods of frame selection are described, one based on Frangi filter, and the other based on detecting parallel curves formed from edges in angiography images. Results are shown by comparison to physician annotation of such key frames on 2D coronary angiograms.