Article
DETECTION OF LUNG CANCER BY USING ARTIFICIAL NEURAL NETWORKS
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 image's entropy. We can determine whether or not the patient has lung cancer by getting the values of entropy, contrast, and energy.
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