Automated thresholding of lung CT scan for Artificial Neural Network based classification of nodules

In this paper, the threshold value of overlapped circular region is calculated. The lung volume is segmented by thresholding, lung lobe extraction, hole filling and contour corrected. The regions of interest are segmented from extracted lung volume. The candidate nodules are selected from the ROIs. The features of candidate nodules are extracted. Artificial Neural Network classifier is trained and tested on the dataset. The proposed methodology produces sensitivity of 96.55% with accuracy of 91.87% and 0.40 FP/scan.