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Lung cancer is one of the death threatening diseases among human beings.Early and accurate detection of lung cancer can increase the survival rate fromlung cancer. Computed Tomography (CT) images are commonly used for detectingthe lung cancer.Using a data set of thousands of high-resolution lung scanscollected from Kaggle competition [1], we will develop algorithms thataccurately determine in the lungs are cancerous or not. The proposed systempromises better result than the existing systems, which would be beneficial forthe radiologist for the accurate and early detection of cancer. The method hasbeen tested on 198 slices of CT images of various stages of cancer obtainedfrom Kaggle dataset[1] and is found satisfactory results. The accuracy of theproposed method in this dataset is 72.2%

Lung Cancer Detection and Classification based on Image Processing and Statistical Learning