Recognition of lung cancer using machine learning mechanisms with fuzzy neural networks

Abstract

Location of lung disease is the most fascinating exploration zone of specialist's in beginning times. The proposed framework is intended to identify lung tumor in early stage in two phases. The proposed framework comprises of numerous means, for example, picture securing, prehandling, binarization, thresholding, division, feature extraction, and neural system identification. At first Input lung CT pictures to the framework and afterward they went through the picture pre-preprocessing stage by utilizing some picture handling systems. In first stage, Binarization procedure is utilized to change over twofold pictures and after that contrast it with edge incentive with identifying lung tumor growth. In second stage, division is performed to portion the lung CT picture and a solid component extraction technique has been acquainted with removing some critical elements of sectioned pictures. Separated features are utilized to prepare the neural system lastly the framework. The execution of the proposed framework demonstrates acceptable outcomes and proposed technique gives 96.67 % exactness.