Segmentation and Analysis of CT Chest Images for Early Lung Cancer Detection

In this paper an enhanced method of Hopfield Artificial Neural Network Classifier model is proposed to segment extracted lung regions from human chest Computer Tomography images. The images are acquired using Computer Tomography imaging techniques from normal subjects and others as candidates for lung cancer diagnosis. A combination of bit-planes of each pixel are used to enhance edges' detection of lung region lobes. Three diagnostic rules are verified as well defined filters of candidate cancerous regions from the status of candidate to false or true positive status.