LUNG CANCER STAGES PREDICTION

Abstract

The identification of lung cancer at the early stage is very demanding and difficult task
due to construction of the cell. The cancer grows in the body when cancerous cells start
to develop uncontrollably. The image processing plays vital role in the prediction of
lung cancer at early stage which is also helpful in treatment to avoid the lung cancer.
This proposed system is developed to detect lung cancer at early stage with the help of
image processing techniques and artificial neural network classifier to design computer
based diagnosis system. In this system, during the preprocessing step, several image
enhancing techniques, masks are applied using morphological operations and
thresholding technique, which eliminates background and surrounding tissue. Region
of interest (ROI) is calculated using region based segmentation algorithm. Circle fit
algorithm is used to extract the desired nodule. Radius, Mean Intensity, Area, Euler
Number and ECD features are extracted in feature extracting step. Finally, Back
propagation algorithm is used to train Artificial Neural Network (ANN) in
categorization stage.