Loading content...
The paper presents an automated lung cancer detection system using CT images. Preprocessing, GLCM-based feature extraction and a hybrid CNN-ELM classifier are employed, achieving 95.38% accuracy for automated lung cancer detection.
Early detection of lung nodules is important for timely intervention and improved outcomes. CT imaging is widely used, but the growing volume of images makes manual classification increasingly difficult, motivating automated image-processing approaches.