Early Detection of Liver Cancer using Soft Computing - A Review

Liver is the important parts of the human beings as well as a sixth dangerous disease in the world is liver cancer tumors. There are two types of liver tumors such as malignant and benign. The benign type of tumors is the initial stage tumors and they cause no harm but there is other type called malignant which is the advanced stage. So the detection and diagnosing of malignant tumor is very important. The early detection of liver cancer tumor is very essential to provide the timely treatment so that the probability of curing the disease increases. The manual analysis of the tumor samples is time overwhelming, inaccurate and needs very efficiently trained persons to avoid diagnostic errors. So based on all these parameters into consideration, a soft computing based image mining approach of detecting these tumors in early stage were proposed. The image mining techniques such as classification and clustering are applied with Soft computing techniques such as fuzzy sets, neural networks, genetic algorithms, and rough sets. The objective of this study is to improve the liver cancer prediction with the application of soft-computing techniques.