RETRACTED ARTICLE: Improved performance accuracy in detecting tumor in liver using deep learning techniques

Abstract

One of the foremost decease causes in the world is the Liver Cancer. Using practical radiology the liver lesions can be determined with accurate dramatization, due to the hurt caused by wound or disease, those ranges of tissues are damaged the body are liver lesions Those anomalous tissues which are found in the liver are referred as liver lesions. These damaged regions having different intensities of pixel can be recognized by differentiating it from other regions, in the CT scan. The most prohibitive, difficult and time-consuming task is physical cleavage of this CT scan in proper clinical treatment. On the other hand, automatic segmentation is identical challenging task, due to several factors, including liver stretch over 150 slices in a CT image, having small ferocity conflict between lesions and other nearby similar tissues and indefinite shape of the lesions is to detected An important prerequisite task before any surgical intervention is liver tumors segmentation. This paper reviews a variety of liver tumor detection algorithms and methodologies used for liver tumor analysis. The proposed deep learning approach such as Probabilistic neural network is proposed to detect the liver tumor and diagnose with the experimental results and it is compared with different methodologies.