Soorajkumar, R.Krishna, Kumar, P.Girish, D.Rajan, J.2020-03-302020-03-3020162016 International Conference on Signal Processing and Communications, SPCOM 2016, 2016, Vol., , pp.-https://idr.nitk.ac.in/handle/123456789/8089Medical ultrasound images are generally corrupted with a type of signal dependent noise called speckle. The major reason for the speckle in ultrasound images is the constructive or destructive interference of ultrasound waves. The granular pattern of the speckle noise degrades the image and hinders the information present in it. In this work, we developed an improved speckle denoising method using a fourth order partial differential equation (PDE) model by integrating Edge Noise Interior method in it. Edge Noise Interior (ENI) method preserves the edges and counts the number of homogeneous pixels in the neighbourhood to classify the edges. Furthermore, a maximum likelihood technique is used to estimate and remove the bias in the denoised images. The proposed method is compared against other existing methods and validated for both simulated as well as real ultrasound images. The proposed method outperforms other state-of-the-art methods in terms of qualitative and quantitative analysis. � 2016 IEEE.Book chapter