Detection Of Liver Diseases In Computed Tomography Scan Images Using Artificial Neural Networks

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ABSTRACT

Liver is one of the most important organ in the human body, it performs a

variety of vital functions. Liver cancer is a pathological disorder of the human

that affects around 50 million people worldwide. The early detection and

diagnosis of liver cancer is very important to facilitate the treatment process.

The objective of this study is to design and develop an automated system for

liver CT images diagnosis as normal or abnormal to help physicians in their

diagnosis and treatment plan.

The proposed system performs an automatic segmentation of liver region after

applying different enhancement techniques, then the features are extracted

from the segmented liver region using Haralick’s feature, this step is followed

by features selection and reduction to choose the best representative features.

As final step selected features are classified into two classes normal or

abnormal. Artificial Neural Network (ANN) and Support Vector Machine (SVM) are

applied in the classification step, then the results of them are compared to each other to select the best one and use it to design an automated system.

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Detection Of Liver Diseases In Computed Tomography Scan Images Using Artificial Neural Networks

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