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A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography

by Gunasundari S, Janakiraman S
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 11
Year of Publication: 2013
Authors: Gunasundari S, Janakiraman S
10.5120/12927-9800

Gunasundari S, Janakiraman S . A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography. International Journal of Computer Applications. 74, 11 ( July 2013), 7-12. DOI=10.5120/12927-9800

@article{ 10.5120/12927-9800,
author = { Gunasundari S, Janakiraman S },
title = { A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 11 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number11/12927-9800/ },
doi = { 10.5120/12927-9800 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:57.635653+05:30
%A Gunasundari S
%A Janakiraman S
%T A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 11
%P 7-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Liver diseases are considered seriously because liver is a vital organ to human beings. Computer aided liver analysis is a technique that can help radiologists to accurately identify diseases that can help in reducing the risk of liver surgery. The computer aided diagnosis (CAD) system consists of the segmentation of liver and lesion, extraction of features from a lesion and characterization of liver diseases by means of a classifier. In the last decade, the use of many segmentation techniques and classifier systems have been proposed by many authors with the intention to increase the performance of CAD systems This article focuses on various textural analysis methods used so far for the classification of liver diseases from abdominal Computed Tomography scans. It reviews the techniques and results of the various methods are analyzed and summarized. The future direction for the research is also discussed

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Index Terms

Computer Science
Information Sciences

Keywords

CT Textural Features Neural Network Co occurrence Matrix CAD Feature Selection Liver

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