A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
Knowledge-based adaptive thresholding segmentation of digital subtraction angiography images
Image and Vision Computing
Computer Methods and Programs in Biomedicine
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We present an efficient algorithm for vessel segmentation of Digital Subtraction Angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By separating vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for the parameters used are also reported and discussed.