Novel approach for automatic mid‐diastole frame detection in 2D echocardiography sequences for performing planimetry of the mitral valve orifice

Abstract

The mitral valve orifice area is a reliable measure for evaluating mitral valve stenosis (MS) severity, which is obtained by the planimetry of the mid-diastole frame in the echocardiography sequences. Since the manual method for determining this frame is time-consuming and user-dependent, a novel automatic method has been proposed in this study. First, the region of interest (ROI) containing the mitral valve orifice region is detected using circular Hough transform and k-means algorithms. Then, the dimension reduction method is applied to the ROI of each frame to map it into a point in a 2D space. The performance of the local linear embedding (LLE), isometric mapping, kernel principal component analysis (PCA), and linear PCA algorithms has been evaluated in this study. Finally, a distance curve is obtained by calculating the Euclidean distance between consecutive points in 2D space, and the mid-diastole frame is determined by interpreting this curve. The proposed algorithm was validated using 2D echocardiography of the 20 MS patients. Finally, the LLE method showed the best result, and the average frame difference for 20 cases using the proposed method compared with the gold standard (the echo-cardiologist opinion) was 1.40.