Comparative Approach for Speckle Reduction in Medical Ultrasound Images

Medical images are often deteriorated by noise due to various sources of interferences and other phenomena that affect the measurement processes in an imaging and acquisition system. Speckle noise is a random mottling of the image with bright and dark spots, which obscures fine details and degrades the detectability of low-contrast lesions. Speckle noise occurrence is often undesirable, since it affects the tasks of human interpretation and diagnosis. On the other hand, its texture carries important information about the tissue being imaged. Speckle filtering is thus a critical pre-processing step in medical ultrasound imagery, provided that the features of interest for diagnosis are not lost. In ultrasound images, the speckle energy is comparable to the signal energy in a wide range of frequency bands. Several speckle reduction techniques are applied to ultrasound images in order to reduce the noise level and improve the visual quality for better diagnoses. The optimum choice of wavelet bases for ultrasound images is investigated in this study. In order to realize a fair comparison, the same analysis for three frequency values is used. The comparison proves that the wavelet transform gives a much better result than both median filtering and homomorphic Wiener filtering methods for speckle reduction of ultrasound images.