  Automatic identification of proper image frames at the end-diastolic (ED) and
end-systolic (ES) frames during the review of invasive coronary angiograms
(ICA) is important to assess blood flow during a cardiac cycle, reconstruct the
3D arterial anatomy from bi-planar views, and generate the complementary fusion
map with myocardial images. The current identification method primarily relies
on visual interpretation, making it not only time-consuming but also less
reproducible. In this paper, we propose a new method to automatically identify
angiographic image frames associated with the ED and ES cardiac phases by using
the trajectories of key vessel points (i.e. landmarks). More specifically, a
detection algorithm is first used to detect the key points of coronary
arteries, and then an optical flow method is employed to track the trajectories
of the selected key points. The ED and ES frames are identified based on all
these trajectories. Our method was tested with 62 ICA videos from two separate
medical centers (22 and 9 patients in sites 1 and 2, respectively). Comparing
consensus interpretations by two human expert readers, excellent agreement was
achieved by the proposed algorithm: the agreement rates within a one-frame
range were 92.99% and 92.73% for the automatic identification of the ED and ES
image frames, respectively. In conclusion, the proposed automated method showed
great potential for being an integral part of automated ICA image analysis.
