Stent Shape Estimation through a Comprehensive Interpretation of Intravascular Ultrasound Images

F. Ciompi, S. Balocco, C. Caus, J. Mauri and P. Radeva

in: Medical Image Computing and Computer-Assisted Intervention of Lecture Notes in Computer Science, 2013, pages 345-352


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.