Since the upturn of intravascular ultrasound (IVUS) as an imaging technique for the coronary artery system, much research has been done to simplify the complicated analysis of the resulting images. In this study, an attempt to develop an automatic tissue characterization algorithm for IVUS images was done. The first step was the extraction of texture features. The resulting feature space was used for classification, constructing a likelihood map to represent different coronary plaques. The information in this map was organized using a recently developed geodesic snake formulation, the so-called Stop & Go snake. The novelty of our study lies in this last step, as it was the first time to apply the Stop & Go snake to segment IVUS images.
CITATION STYLE
Brunenberg, E., Pujol, O., ter Haar Romeny, B., & Radeva, P. (2006). Automatic IVUS segmentation of atherosclerotic plaque with stop & go snake. Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 9(Pt 2), 9–16. https://doi.org/10.1007/11866763_2
Mendeley helps you to discover research relevant for your work.