An Efficient Approach for Denoising Ultrasound Images using Anisotropic Diffusion and Teaching Learning Based Optimization
Sumit Kushwaha and Rabindra Kumar SinghElectronics Engineering Department, Kamla Nehru Institute of Technology, Sultanpur, India.
Corresponding Author E-mail: sumit.kushwaha1@gmail.com
Abstract: Medical imaging is an indispensable tool for diagnosis of several complex disorders. In preceding years, advancement in medical imaging have aided in accurate diagnosis by capturing the anatomical images of the human organs without the necessity to surgically treat the human body. A radical medical diagnosis requires accurate results from the imaging modalities that are generally vulnerable to noises, resulting in a blemished image. In case of ultrasounds, the major noise is the speckle noise. Several tissues in the human body are hard that are accountable for producing multiple reflections of the ultrasound waves causing speckle noise which vitiates the quality of the ultrasound images. We present an efficient denoising method for the ultrasound images that will overcome the noising, particularly obtained through speckle noise. This paper adopts Anisotropic Diffusion for denoising of the image. This paper provides additionally the performance analysis of the denoising mechanism using the Teaching-Learning Based Optimization methods to achieve the targeted results. Also, HSOA algorithm is used for this purpose and the results from both the techniques are compared. The technique for denoising proposed in this paper has extensively enhanced the denoising mechanism used in ultrasound images of the liver. While the proposed system is considered to be effective, however the performance of the denoising carried out by the TLBO algorithm concluded that the denoising was over-filtering the image with the additional loss of data.
Keywords: Ultrasound image; Denoising; Anisotropic Diffusion; Teaching–learning based optimization (TLBO) algorithm; Harmony search optimisation algorithm (HSOA) Back to TOC