NDLI: Speckle reduction method for thyroid ultrasound images in neutrosophic domain

Content Provider	IET Digital Library
Author	Koundal, Deepika Gupta, Savita Singh, Sukhwinder
Abstract	Neutrosophy is a useful tool for handling uncertainty associated with the images and widely used in image denoising. Speckle noise is inherent in ultrasound images, which generally tends to reduce resolution and contrast, thereby degrading the diagnostic accuracy. This paper presents a variational method based on Gamma distribution in the neutrosophic domain to improve clinical diagnosis and to enhance quality of ultrasound images. In this method, image is transformed into the neutrosophic (NS) domain via three membership subsets (true, indeterminate and false). Then, the filtering operation is applied based on total variation regularisation to reduce the indeterminacy of the image, which is measured by the entropy of an indeterminate set. The proposed speckle reduction method has been assessed on both the artificial speckle simulated images and real US images. The experimental results reveal the superiority of the proposed method in terms of both quantitatively and qualitatively as compared to other speckle reduction methods reported in the literature. Furthermore, the visual evaluation of despeckled images demonstrates that the proposed method suppresses the speckle noise as well as preserves the textures and fine details.
Starting Page	167
Ending Page	175
Page Count	9
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 2, Feb (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2015.0231
Journal	IET Image Processing
Publisher Date	2016-02-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Artificial Speckle Simulated Image Biology And Medical Computing Biomedical Ultrasonics Clinical Diagnosis Combinatorial Mathematics Computer Vision And Image Processing Technique Despeckled Image False Subsets Filtering Operation Function Theory And Analysis Gamma Distribution Graph Theory Image Denoising Image Enhancement Image Filtering Image Texture Image Textures Indeterminate Subsets Mathematical Analysis Medical Image Processing Neutrosophic Domain Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Probability Theory Set Theory Signal-to-noise Ratio Gain Sonic And Ultrasonic Application Sonic And Ultrasonic Radiation Speckle Noise Suppression Speckle Reduction Method Statistics Stochastic Linearised SCUC Thyroid Ultrasound Image Total Variation Regularisation True Subsets Ultrasound Image Quality Enhancement Variational Method Variational Technique
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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