Published Paper Details:

The liver is the largest gland and largest internal organ in the human body. The abnormal growth of cell in the liver causes liver cancer which is also known as hepatic cancer where, Hepatocellular Carcinoma (HCC). Most of the peoples who have liver tumour were died due to the fact of inaccurate detection. The detection of this tumours is difficult and mostly found at advanced stage which causes life-threatening issues. Hence it is far essential to discover the tumour at an early stage. So, the principle intention of this project is to detect liver cancer at earlier stage using image processing technique. Computer-aided diagnosis from various medical imaging techniques can assist significantly in detecting liver cancer at a very early stage. This project presents an automated method of detecting liver cancer in abdominal CT images and classifying them using the support vector machine (SVM) algorithm. The proposed model consists of several stages where the image is first normalized and pre-processed using a Median filter to remove noise in the image. After histogram equalization of image, the features are extracted based on Discrete wavelet transformation (DWT). Finally, liver CT images are classified implementing support vector machine and segmented results. The software used here is MATLAB.