Abstract
Lung cancer is a fatal disease that takes numerous lives every year around the world. However, detecting this disease in its initial stages can help save the lives of the people. CT imaging is the best technique used for imaging in the field of medical sciences. It is used by doctors but it is hard for medical examiners to decipher and recognize cancer through the computer-assisted tomography scan images. Hence, Computer-aided diagnosiswill be very supportive for the medical examiners to identify and recognize the cancerous nodules in cells precisely. The primary agenda of the project is to assess diverse computer based methods, explore present finest method, deduce its limitations and setbacks. Then, proposing a latest model with upgrades and advancements to the present leading model. Techniques appliedfor diagnosis of lung cancerare organized based on theprecision. Numerous methods were surveyedon everystride and the complete limitations and setbacks were identified. A lot of techniques had low precision and few had high precision. But none of those were satisfying. Therefore, our target is to increase the precision of themodel.
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