A bifurcation identifier for IV-OCT using orthogonal least squares and supervised machine learning
The second automated approach to classify hundreds of coronary OCT frames as bifurcation or nonbifurcation. An important step to improve studies of atherosclerotic plaques in bifurcation regions. Geometrical features of vessel cross-section are selected by orthogonal least squares method. The lumen segmentation is comparable to measurements provided by other methods in the literature.
bifurcation orthogonal least squares machine learning segmentation optical coherence tomography intravascular classification