Lung Nodule Detection Using data Mining Techniques
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Date
2014
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Abstract
Lung cancer is one of the most common deadliest diseases, it affects both men and women throughout
the world. Detection of lung cancer at an early stage can increase the survival rate. For accurate detection it needs
to identify efficient features and delete redundancy features among all features. The digital chest film in lung
cancer database is divided into normal, benign and malignant. The normal ones indicate the healthy patients (non
nodules) and can either benign (non-cancerous) and malignant (cancerous). There are five main phases involved
in the proposed work. They are image preprocessing, lung segmentation, nodules detection, feature extraction
and image classification. The segmentation algorithm used is OTSU method. Segmentation method used to do
accurate segmentation of lung region from the digital lung x-ray images. Classification method is used to detect
whether the nodule are either benign or malignant.