A Review on Liver Cancer Detection Techniques

Abstract

In this paper, a detailed review has been done on liver cancer detections and this paper provides details of different techniques that reveal how hybrid intelligent approaches are applied to different categories of cancer detections and treatments. The principle goal of this review is to highlight mostly used features, classifiers, methodologies, key concepts, and their accuracy. Under cancer detection techniques, various types of machine learning algorithms are used such as decision tree, SVM, neural networks, random forest, computer aided detection, genetic algorithms etc. These strategies exert significant effects on liver image characterization and having different accuracy levels. All the long short solutions talked about strategies are provided in this manuscript and it is explored up to various execution measurements.