Asian Journal of Engineering and Technology Innovation

Overcoming the Challenges in Liver Tumor Imaging and Classification

Thejesha B.R, Ms^{. Ni}rmala S. Gupta

1M.Tech Student, Computer Network Engineering, Reva Institute of Technology and Management, Bangalore

2Associate Professor, Dept. of CSE, Reva Institute of Technology and Management, Bangalore

Abstract

Liver disease is one of the leading causes of death today. In particular, liver tumor is increasingly affecting a larger percentage of the population every day. Hence it is imperative to quickly and effectively deal with the disease. A primary step is the identification and classification of the liver tumors. Existing techniques lack the accuracy and efficiency that the treatment demands. A combination of the PHOG and SGLDM algorithms are used in tandem with the SVM classifier to arrive at a more accurate system of detection and classification. The SVM classifier helps automate the entire process. Contemporary literature in the field also supports the efficiency of the SVM technique used in this research.

Keywords:

Segmentation, Ultrasound, SVM classifier, PHOG and SGLDM algorithms.