TY  - JOUR
AU  - David Rotger
AU  - Petia Radeva
AU  - N. Bruining
PY  - 2010//
TI  - Automatic Detection of Bioabsorbable Coronary Stents in IVUS Images using a Cascade of Classifiers
T2  - TITB
JO  - IEEE Transactions on Information Technology in Biomedicine
SP  - 535 – 537
VL  - 14
IS  - 2
N2  - 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%.
UR  - http://dx.doi.org/10.1109/TITB.2009.2017528
N1  - MILAB
ID  - David Rotger2010
ER  -