Segmentation, Detection, and Classification of Liver Tumors for Designing a CAD System

Abstract

Globally cancer is the foremost threat to public health. Out of the world population, the deaths caused by liver cancer are increasing by 3% every year. Liver tumors are the pathological disorders which can be detected with the help of various image processing methods. A Computer-Aided Diagnosis (CAD) system use image processing tools and techniques for detecting liver tumors which acts as an assistance to the radiologists, oncologists, and hepatologists for effective diagnosis. The main objective of this survey is to analyze the available techniques that can aid in developing or designing a CAD system for liver tumors. Various methods and outcome of available techniques for segmentation, detection and classification of liver tumors from Computed Tomography (CT) or Dynamic Contrast-Enhanced Magnetic Resonance (DCE-MR) images are discussed and compared in detail.