Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the late restenosis. These stents made of poly-L-lactic acid cause a very subtle acoustic shadow (compared to the metallic ones) making difficult the automatic detection and measurements in images. In this paper, we propose a novel approach based on a cascade of GentleBoost classifiers to detect the stent struts using structural features to code the information of the different subregions of the struts. A stochastic gradient descent method is applied to optimize the overall performance of the detector. Validation results of struts detection are very encouraging with an average F -measure of 81%. © 2009 IEEE.
|Journal||IEEE Transactions on Information Technology in Biomedicine|
|Publication status||Published - 1 Mar 2010|
- Automatic detection
- Intravascular ultrasound (IVUS)
- Stent struts
Rotger, D., Radeva, P., & Bruining, N. (2010). Automatic detection of bioabsorbable coronary stents in IVUS images using a cascade of classifiers. IEEE Transactions on Information Technology in Biomedicine, 14(2), 535-537. . https://doi.org/10.1109/TITB.2009.2017528