Efficient Lung Nodule Classification Method using Convolutional Neural Network and Discrete Cosine Transform

In today’s medicine, Computer-Aided Diagnosis Systems (CAD) are very used to improve the screening test accuracy of pulmonary nodules. Processing, classification, and detection techniques form basis CAD architecture. this work, we focus on classification step in a system where use Discrete Cosine Transform (DCT) along with Convolutional Neural Network (CNN) perform an efficient method for Combining both DCT CNN, proposed provides high-level that outperforms conventional CNN model.