Texture Based Quality Analysis of Simulated Synthetic Ultrasound Images Using Local Binary Patterns

Abstract

Speckle noise reduction is an important area of research in the field of ultrasound image 10 processing. Several algorithms for speckle noise characterization and analysis have been recently 11 proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods 12 as they can be used to generate a variety of speckle noise models under different interpolation and 13 sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of 14 the chosen methods. However, not much work has been done in the area of modelling synthetic 15 ultrasound images, and in simulating speckle noise generation to get images that are as close as 16 possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images 17 is the requirement for extensive quality assessment for ensuring that they have the texture 18 characteristics and gray-tone features of real images. This paper presents texture feature analysis of 19 synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a 20 set of LBP features for image quality assessment. Experimental results presented in the paper 21 clearly show how these features could provide an accurate quality metric that correlates very well 22 with subjective evaluations performed by clinical experts. 23Keywords: ultrasound image analysis; speckle noise; synthetic ultrasound images; texture features; 24 local binary patterns; image quality assessment 25 26