NDLI: Speckle suppression in medical ultrasound images through Schur decomposition

Content Provider	IET Digital Library
Author	Khan, Adil H. Asad, Jawad F. Al Latif, Ghazanfar
Abstract	A technique based on Schur decomposition to supress the multiplicative (speckle) noise from medical ultrasound images is presented in this study. An image which carries the speckle noise is divided into small overlapping segments, size of these segments depends on the nature of speckle carried by the image and a global covariance matrix is calculated for the whole image by averaging the covariances of all segments. The global covariance matrix is decomposed through Schur decomposition to obtain the orthogonal vectors. A subset of these orthogonal vectors that correspond to largest magnitudes of eigenvalues are selected to filter out the speckle noise from the image. The proposed approach is compared with four benchmark filtering techniques, homomorphic wavelet despeckling, Wiener, Frost and Gamma. Two types of simulated ultrasound images and five types of real ultrasound images of foetal neck, left kidney, right kidney, musculo skeletal nerve and lymph node are tested. The proposed approach performed maximum suppression of speckle noise in all types of the images with optimal resolution and edge detection. The despeckling performance of the proposed approach is even better compared with the benchmark schemes once the speckle noise is rough, which is usually the case for soft tissue.
Starting Page	307
Ending Page	313
Page Count	7
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 3, Mar (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0411
Journal	IET Image Processing
Publisher Date	2017-10-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Biological Tissues Biology And Medical Computing Biomedical Ultrasonics Computer Vision And Image Processing Technique Covariance Matrices Edge Detection Eigen Values And Eigen Function Eigenvalues Magnitudes Filtering Method in Signal Processing Filtering Theory Foetal Neck Global Covariance Matrix Graph Theory Image Denoising Image Recognition Kidney Left Kidney Lymph Node Medical Image Processing Medical Ultrasound Image Multiplicative Noise Suppression Musculo Skeletal Nerve Optimal Resolution Orthogonal Vector Overlapping Segments Patient Diagnostic Method And Instrumentation Right Kidney Schur Decomposition Set Theory Simulated Ultrasound Image Sonic And Ultrasonic Radiation Speckle Speckle Suppression Vector
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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