Abstract
We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm. © 2013 Springer-Verlag.
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CITATION STYLE
Ciompi, F., Balocco, S., Caus, C., Mauri, J., & Radeva, P. (2013). Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8150 LNCS, pp. 345–352). https://doi.org/10.1007/978-3-642-40763-5_43
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