Angular feature vector based speckle denoising technique for ultrasound medical images

An ultrasound image provides the radiologist with noninvasive, low cost, and real-time images that can help them in diagnosis, planning and therapy. However, although the human eye is able to derive the meaningful information from these images, automatic processing is very difficult because of the noise and artifacts present in the image. This paper proposes different filtering techniques based on feature vector based statistical methods for the removal of speckle noise. In this work, we propose to extend the current hybrid median filter technique to deal with the speckle noise present in the Ultrasound images. Metrics like Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE) and Structural Similarity Index Measurement (SSIM) are used to evaluate the efficiency of the proposed work. Experimental results and performance analysis shows promising results when compared with existing methods.