Diagnosis Lung Samples By Fuzzy Logic

Abstract

Lung cancer take into account the most famous eventful cancers in the whole world, with the small number of who will be saved after doctors individuate, with gradual growth in number of deaths every day. Lung cancer is cause due to uncontrolled increases of abnormal cells in one or both lungs. The best way to protection from this danger disease is to detect it early, the early detection gives higher chance of successful treatments. The recognition of lung cancer in early stage is difficult because the cancer cells cause much dangerous effect due to their overlapped structure. In this study we proposed a diagnosis system to detect lung cancer based on stages of feature extraction from the image, this stage uses a significant techniques and algorithms to excommunication multiple desired portions or form (features) of the image and use this features as input to fuzzy logic to classify the normal and abnormal images.