Hierarchical segmentation and tracking of coronary arteries in 2D X-ray Angiography sequences

Coronary arteries (CA) segmentation from an angiographic sequence is essential to guide the cardiologists during percutaneous interventions for the treatment and diagnosis of pathologies. Segmentation of the CA from X-ray angiograms is a very challenging problem due to the changes in contrast in the sequence in addition to the CA's complex topology. In this paper, we propose a hierarchical segmentation method that extends the Vessel Walker model using a temporal prior and multiscale information to extract CA with a higher level of accuracy. In this method, the vessel located in frame I
^t
at time t is extracted by utilizing the segmentation result at frame I
^t−1
together with Histogram of Oriented Gradient (HOG) features and a shape matching technique. Our experiments conducted on five paediatric angiograms have shown promising qualitative and quantitative results with a mean Dice coefficient of 64% and 53% Recall and 85% in Precision.