Detection and Classification of Lung Cancer Using CNN Models

Lung cancer has the maximum number ofmorbidity and mortality globally. Early detection ofpulmonary nodules in the lungs can significantly decrease the incidence of lung cancer. But, detecting small nodules in medical images is extremely difficult due to the vast variation in their shape, size, and location. Additionally, distinguishing between lung cancer and other lung diseases such as pneumonia, tuberculosis, and COVID-19, which typically affect the same regions of the lungs, can lead to diagnostic ambiguity. This complexity makes it difficult to determine the precise treatment. To address this issue, we can develop an automated model to classify CT images according to the type of disease. This approach will facilitate more accurate diagnoses and improve treatment outcomes.