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.