Editorial - Journal of Neuroinformatics and Neuroimaging (2021) Volume 6, Issue 2
Using an improved teo algorithm and an ann for diagnosis of lung cancer.
Lung cancer is responsible for a quarter of all cancer fatalities. Early detection and treatment of this condition, according to studies, is the most effective strategy to extend patient life expectancy. The use of automatic and optimal computer-aided detection for lung cancer is proposed in this research. The procedure begins by normalising and denoising the input images in a pre-processing step. After that, Kapur entropy maximisation and mathematical morphology are used to segment lung areas. For the final evaluations, 19 GLCM features are collected from the segmented images. The photos with the highest priority are then chosen to reduce the system's complexity.Author(s): Shawn Kruger