Automatic Detection of Lung Cancer Identification using ENNPSO Classification

The main source of lung cancer is to gasping the tobacco smoke regularly, which affects around 90% of lung cancers. Cancer cells are to be carried to and from the lungs within the blood or lymph fluid ambience the lung tissue. Early diagnosis and treatment can save life. In this, the image processing techniques have been utilized to identify the lung cancer. Initially, the CT scan image is pre-processed for removing the unwanted signals and smoothing them by employing Improved Kaun Filter (IKF). Subsequently, the preprocessed image is portioned by an Active contour method to get exactness of segmented results. Next, specific features are extracted to raise the anticipated accuracy. At last, the tumour has been categorized by Elman Neural Network (ENN) and weights are optimized with PSO and compared the accuracy results with SVM, RBFN and ANFIS.