NDLI: Atheromatic TM : Symptomatic vs . Asymptomatic Classification Of Carotid Ultrasound Plaque using a combination of HOS , DWT & Texture U

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Atheromatic TM : Symptomatic vs . Asymptomatic Classification Of Carotid Ultrasound Plaque using a combination of HOS , DWT & Texture U

Content Provider	Semantic Scholar
Author	Acharya, Rajendra Kumar Faust, Oliver Alvin, Ang Peng Chuan Ganapathy Krishnamurthi Seabra, Carolina Ribeiro Sanches, João Suri, Jasjit S.
Abstract	—Quantitative characterization of carotid atheroscle-rosis and classification into either symptomatic or asymptomatic is crucial in terms of diagnosis and treatment planning for a range of cardiovascular diseases. This paper presents a computer-aided diagnosis (CAD) system (Atheromatic™, patented technology from Biomedical Technologies, Inc., CA, USA) which analyzes ultrasound images and classifies them into symptomatic and asymptomatic. The classification result is based on a combination of discrete wavelet transform, higher order spectra and textural features. In this study, we compare support vector machine (SVM) classifiers with different kernels. The classifier with a radial basis function (RBF) kernel achieved an accuracy of 91.7% as well as a sensitivity of 97%, and specificity of 80%. Encouraged by this result, we feel that these features can be used to identify the plaque tissue type. Therefore, we propose an integrated index, a unique number called symptomatic asymptomatic carotid index (SACI) to discriminate symptomatic and asymptomatic carotid ultrasound images. We hope this SACI can be used as an adjunct tool by the vascular surgeons for daily screening.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://users.isr.ist.utl.pt/~jmrs/research/publications/myPapers/2011/2011_EMBC_Acharya,.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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