Lung cancer is one of the major and most dangerous diseases in the world and early diagnosis and treatment can save lives. CT scan image is the best technique in the medical field for finding various diseases, it is difficult for finding the diseases for doctors to interpret and identify the cancer using CT scan images. In these cases, computer-assisted diagnosis can be helpful for doctors to identify the cancer cells. In recent research numerous computational models and algorithms using image processing techniques and machine learning approaches have been implemented. In this paper, to proposed different computational techniques to analyze the images using the best technique at the moment and find out its limitations and disadvantages, and finally propose a new model which is used to improve the accuracy performance. The image processing techniques were analyzed at each step and disadvantages were identified. In this research, found that some of the instances have low accuracy, and some have higher accuracy. Numerical illustrations are also provided to prove the results and discussion with research aims to increase accuracy.

CT Scan Image, Lung Cancer Detection, Image Processing, Pre-processing, and Machine Learning.