Lung tumor is a progressive disease containing abnormal cells leading to cancer. The abnormality present devastates the proper regular performance and functioning of lungs. Automatic diagnosis system in medical imagining has increased the survival rate of lung patients at early stage from 20 percent to 70 percent based on https://chow420.com/forum/chowpods-smart-cbd-vending-machines-near-you-NjAz 5 years survey since it provides the appropriate results at the right time. (Gajdhane & Deshpande, 2014). The survival rate prediction is alarming and the necessary factor which proved to help in proper treatment and diagnosis of lung cancer patient (Hawkins et al., 2014). There are two major types of lung carcinoma broadly subdivided into nonsmall cell lung cancer and small cell lung cancer. The nonsmall cell lung carcinomas subtypes are squamous cell carcinoma, adeno carcinoma and large cell carcinoma (Patil & Jain, 2014). The prognosis of lung Tumor is the most challenging task as the cells are assembled on each other therefore it is essential to determine the features and structure of diagnosed image (Tiwari, 2016). https://chow420.com/forum/chow420-hemp-general-store-for-vetted-cbd-prod... The automated lung nodule detection on medical images involves image enhancement, image segmentation and feature extraction to classify the stages of tumor so that proper planning of treatment could be accomplished on lung cancer patient (Tariq et al., 2013).
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