P. GOVARDHAN, P. SIVA KRISHNA, P. PAVAN SRINIVAS, T. JAGADEESH, K. MANIDEEP 03 02 In this study we created a unique modular neural network for precise human lung cancer diagnosis we have taken the MRI reports of the patients and then we have evaluated the MRI images with the use of image processing techniques and neural networks to check whether the patient has been impacted by lung cancer or not In order to improvise the MRI images for analysis we are grayscale function for making the images fit for the lung cancer In order to determine the contrast and energy of the image which are crucial factors in identifying lung cancer we have applied the neural fuzzy classifications method We have used the feature extraction approach to determine the images entropy We can determine whether or not the patient has lung cancer by getting the values of entropy contrast and energy Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026