Automated classification of liver disorders using ultrasound images

FAA Minhas, D Sabih, M Hussain - Journal of medical systems, 2012 - Springer
Journal of medical systems, 2012Springer
This paper presents a novel approach for detection of Fatty liver disease (FLD) and
Heterogeneous liver using textural analysis of liver ultrasound images. The proposed
system is able to automatically assign a representative region of interest (ROI) in a liver
ultrasound which is subsequently used for diagnosis. This ROI is analyzed using Wavelet
Packet Transform (WPT) and a number of statistical features are obtained. A multi-class
linear support vector machine (SVM) is then used for classification. The proposed system …
Abstract
This paper presents a novel approach for detection of Fatty liver disease (FLD) and Heterogeneous liver using textural analysis of liver ultrasound images. The proposed system is able to automatically assign a representative region of interest (ROI) in a liver ultrasound which is subsequently used for diagnosis. This ROI is analyzed using Wavelet Packet Transform (WPT) and a number of statistical features are obtained. A multi-class linear support vector machine (SVM) is then used for classification. The proposed system gives an overall accuracy of ~95% which clearly illustrates the efficacy of the system.
Springer
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