Detection of cardiac boundaries in echocardiographic images using a customized order statistics filter

Order statistics filters are nonlinear filters that suppress impulsive and Gaussian noise while preserving edges. These features are particularly useful for cardiac boundary detection in ultrasound images. Based on these facts, we have analyzed performance of a combined ranked order statistics filter. The filter subtracts ranks of ordered highest and lowest intensity values of pixels encompassed in a filter window. The rank extent and window size selection allow adjustment of filter properties for a particular application. Increasing the rank fosters the low-pass characteristics of the filter. Increasing the window size supports noise removal but reduces anatomic selectivity. The filter highlights cardiac boundaries in clinical echocardiograms with intensity proportional to the local probability of a presence of the boundary.