抽象的

Lung cancer segmentation and diagnosis of lung cancer staging using MEM (modified expectation maximization) algorithm and artificial neural network fuzzy inference system (ANFIS)

Lavanya M, Muthu Kannan P

Medical image processing plays a major role in advancing treatment planning, identification of disease and guiding for surgery. Lung cancer is one among the dangerous diseases that leads to death of most human beings due to uncontrolled growth in the cell. This research area is finding more importance among researchers is that because the available methods for lung cancer detection are very painful. So the automatic detection of lung nodule of computer tomography (CT) is finding more importance among researchers. Though there are a number of methods available for segmentation of lung nodules each method has its drawbacks because of the divergence that exists in lung nodule. The proposed method is the detection of lung nodules using MEM algorithm and classification is based on Artificial Neural Network Fuzzy Inference System (ANFIS) experimental results illustrate in an improvement of accuracy and reduction of false positive results. A comparative analysis is performed with FCM and FLICM algorithms to show the superior nature of MEM.