An automatic labeling bifurcation method for intracoronary optical coherence tomography images

Vessel branchings are critical vascular locations from the clinical point of view. In these sites, the arterial hemodynamic plays a relevant role in the progression of atherosclerosis, an important vascular pathology. In this paper, a fully automatic approach for the bifurcation classification in human Intravascular Optical Coherence Tomography (IV-OCT) sequences is introduced. Given the lumen contours, the method is capable of labeling the bifurcation slices. A geometric feature extraction was performed and the Forward Regression Orthogonal Least Squares method (FROLS) was applied to analyze the best features and to determine the appropriated weights in a binary classifier. A cross-validation scheme is applied in order to evaluate the performance of the classification approach and the results have shown a sensitivity of 86% and specificity of 92% to FROLS.