@incollection{eprints2239,
            note = {21st Signal Processing and Communications Applications Conference (SIU), Haspolat, Cypros, 24-26 April 2013 },
       publisher = {IEEE},
          author = {Ilkay Oksuz and Devrim Unay and Kamuran Kadipasaoglu},
       booktitle = {Proceedings of the 21st Signal Processing and Communications Applications Conference (SIU)},
           month = {April},
           pages = {1--4},
           title = {Region growing on frangi vesselness values in 3-D CTA data},
            year = {2013},
        keywords = {Coronary Arteries; Frangi Vesselness; Medical Image Processing; Region Growing; Vessel Segmentation},
             url = {http://eprints.imtlucca.it/2239/},
        abstract = {In cardiac related diagnostic methods, the shape and curvature of coronary arteries is essential. Consequently, one of the most important requirements for Computer Aided Diagnosis (CAD) Systems is automated segmentation of vasculature. In this paper, we propose a new hybrid algorithm, which segment the coronary arterial tree in CTA images by merging methodologies-, namely, Region Growing and Frangi Approach. The algorithm first runs a region growing on Frangi vesselness values and subsequently optimizes the results with several threshold values. Comparison of the present results with optimal results of existing segmentation algorithms reveals that the proposed approach outperforms its predecessors. The diagnostic accuracy of the algorithm will next be validated on the segmentation of coronary arteries from real CT data.}
}