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.
