Automatic detection of inter-frame motion in echocardiographic images

Signal averaging of echocardiographic frames acquired over multiple cardiac cycles has been used to improve image quality. However, misalignment of frames from respiration, transducer or patient movement, and irregular cardiac contraction affects the quality of the resultant averaged image. A motion detection system has been developed using inter-frame subtraction and statistical pattern recognition techniques. Automatic selection of frames exhibiting significant motion in a canine cardiac model compare favorably to manual selection by cardiologists (phi = 0.94) in a test set of 103 images. This method, combined with signal averaging, has resulted in an improvement in image quality.