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Erschienen in:
2011 | OriginalPaper | Buchkapitel
2D Vessel Segmentation Using Local Adaptive Contrast Enhancement
verfasst von : Dominik Schuldhaus, Martin Spiegel, Thomas Redel, Maria Polyanskaya, Tobias Struffert, Joachim Hornegger, Arnd Doerfler
Erschienen in: Bildverarbeitung für die Medizin 2011
Verlag: Springer Berlin Heidelberg
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2D vessel segmentation algorithms working on 2D digital subtraction angiography (DSA) images suffer from inhomogeneous contrast agent distributions within the vessels. In this work, we present a novel semi-automatic vessel segmentation method based on local adaptive contrast enhancement. Either a forward projected 3D centerline or a set of manual selected seed points define the vessel branches to be segmented on the image. The algorithm uses bilateral filtering followed by local contrast enhancement to eliminate intensity inhomogeneity within the vessel region that is caused by unequally distributed contrast agent. Our segmentation algorithm is extensively evaluated on 45 different DSA images and exhibits an average Hausdorff distance of 22 pixels and sensitivity of 89 %.