CAD system for lung nodules detection using wavelet-based approach and intelligent classifiers

摘要

Lung nodules are generally higher indicators of lung cancer. Detected at an early stage, their treatment could be easier and patient chances for survival are improved. This research aims to establish a methodology for the automated identification of lung nodules using image processing and pattern recognition techniques. The automatic system that we propose in this paper includes a pre-processing stage, a nodule characterization stage and a classification stage. The proposed preprocessing system aims to delimit the lung tissue by deleting all the unnecessary regions. The characterization process is based mainly on the analysis of the textural properties of the nodules. The gaussian density calculation in the wavelet domain allows for an efficient segmentation of the current nodules. Then, a comparative classification method based on SVM classifier, bayesian regularization networks and ANFIS classifier, on the LIDC database, is proposed, showing the robustness of the approach proposed.