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J. Imaging 2018, 4(1), 3; doi:10.3390/jimaging4010003 (registering DOI)

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

1
Department of Computer Science and Software Engineering, University of Canterbury, Christchurch 8041, New Zealand
2
Radiology Services, Canterbury District Health Board, Christchurch 8140, New Zealand
This paper is an extended version of our paper published in (Speckle Simulation and Quality Evaluation of Synthetic Ultrasound Images. In Communications in Computer and Information Science, Processing of the Medical Image Understanding and Analysis. (MIUA), Edinburgh, UK, 11–13 July 2017; Valdés Hernández,M., González-Castro, V., Eds.; Springer: Cham, Switzerland, 2017; Volume 723, pp. 74–85.
*
Author to whom correspondence should be addressed.
Received: 28 October 2017 / Revised: 14 December 2017 / Accepted: 18 December 2017 / Published: 21 December 2017
(This article belongs to the Special Issue Selected Papers from “MIUA 2017”)
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Abstract

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modeling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts. View Full-Text
Keywords: ultrasound image analysis; speckle noise; synthetic ultrasound images; texture features; local binary patterns; image quality assessment ultrasound image analysis; speckle noise; synthetic ultrasound images; texture features; local binary patterns; image quality assessment
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Singh, P.; Mukundan, R.; De Ryke, R. Texture Based Quality Analysis of Simulated Synthetic Ultrasound Images Using Local Binary Patterns. J. Imaging 2018, 4, 3.

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