Automated tracking of the vascular tree in dsa images using a double-square-box region-of-search algorithm

We have developed a double-square-box region-of-search algorithm for semi-automated tracking of the vascular tree. Starting from a user-specified point, the algorithm accurately and automatically tracks the connected vessels in the entire vascular tree. In this study, we used the tracking algorithm in conjunction with the iterative deconvolution technique to obtain accurate vessel sizes and contrasts along the vessels being tracked. The tracking algorithm used the vessel size information to generate square-box regions of search for subsequent tracking points. Both the vessel size and the vessel contrast were monitored to determine the point at which tracking of a particular vessel would be terminated. The vessel sizes and contrasts along the vascular tree will be useful for further quantitative analysis of the vessels. At present, the algorithm accurately tracks the vascular tree into regions in which the ratio between the vessel contrast and the root mean square (RMS) noise is approximately 3 for vessel sizes of 0.5 mm or more.