Lung Tumor detection based on Artificial Neural Network

Abstract

Lung Tumors can be kindhearted or threatening. Kindhearted tumors can be evacuated and don't spread to the pieces of the body. Threatening tumors regularly can spread forcefully and cause passing. Early finding of lung disease can help specialists to treat patients and keep them alive. The illnesses, for example, pleural emission and ordinary lung are distinguished and arranged right now. This paper presents a PC helped grouping Method in Computer Tomography (CT) Images of lungs created utilizing ANN. The reason for the work is to identify and order the lung infections by viable component extraction through a Transform method called Gabor Wavelet and LBP. NN classification has been designed for Artificial Neural Network of ILD patterns, by which malignant melanoma and benign lung cancer could be detected and classified and the condition of the lung can be identified as normal or abnormal.