Stent Shape Estimation through a Comprehensive Interpretation of Intravascular Ultrasound Images^*

Francesco Ciompi^1,2, Simone Balocco^1,2, Carles Caus³, Josepa Mauri³, and Petia Radeva^1,2

¹Dep. of Applied Mathematics and Analysis, University of Barcelona, Spain
fciompi@cvc.uab.es

²Computer Vision Center, Campus UAB, Bellaterra, Barcelona, Spain

³Hospital Universitari “Germans Trias i Pujol”, Badalona, Spain

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.

Keywords: IVUS, Stent detection, Stacked Sequential Learning

^*This work was supported in part by the MICINN Grants TIN2009-14404-C02.

LNCS 8150, p. 345 ff.

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