Paper Info
Title
Despeckle Filtering For Multiscale Amplitude-Modulation Frequency-Modulation (Am-Fm) Texture Analysis Of Ultrasound Images Of The Intima-Media Complex
Abstract
The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Typically, the IMT grows with age and this is used as a sign of increased risk of CVD. Beyond thickness, there is also clinical interest in identifying how the composition and texture of the intima-media complex (IMC) changed and how these textural changes grow into atherosclerotic plaques that can cause stroke. Clearly though texture analysis of ultrasound images can be greatly affected by speckle noise, our goal here is to develop effective despeckle noise methods that can recover image texture associated with increased rates of atherosclerosis disease. In this study, we perform a comparative evaluation of several despeckle filtering methods, on 100 ultrasound images of the CCA, based on the extracted multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) texture features and visual image quality assessment by two clinical experts. Texture features were extracted from the automatically segmented IMC for three different age groups. The despeckle filters hybrid median and the homogeneous mask area filter showed the best performance by improving the class separation between the three age groups and also yielded significantly improved image quality.
Year
DOI
Venue
2014
10.1155/2014/518414
INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGING
Keywords
Field
DocType
bioinformatics,biomedical research
Data mining,Computer science,Image quality,Artificial intelligence,Speckle noise,Computer vision,Pattern recognition,Image texture,Filter (signal processing),AM/FM/GIS,Amplitude modulation,Frequency modulation,Ultrasound
Journal
Volume
ISSN
Citations 
2014
1687-4188
3
PageRank 
References 
Authors
0.38
21
6
Name
Order
Citations
PageRank
C P Loizou122820.37
V. Murray219716.47
Marios S. Pattichis334149.71
Marios Pantziaris423421.31
Andrew Nicolaides522017.14
Constantinos S. Pattichis638243.89