Many image processing methods start with an important first step called picture thresholding, which aids in accurate image segmentation and effective prediction. The Sine Cosine Technique is a meta heuristic optimization algorithm that beats several traditional algorithms due to its special premise. Lung cancer CT images were employed in this study because it is one of the most lethal diseases and accounts for a substantial number of fatalities globally. This work demonstrates the application of the Otsu multi thresholding objective function and Sine Cosine nature inspired optimization algorithms on computed tomography (CT) pictures of lung cancer. The suggested method leverages the SCA algorithm's object function, which aids in the selection of elite candidates, to apply the Otsu multi thresholding technique to a CT image.