A Hybrid Method For Detection Of Lung Cancer Image Using Threshold Technique And KNN Algorithm

Lung cancer is a leading cause of death worldwide due to late diagnosis and inefficient detection methods. Accurate, early detection significantly improves patient outcomes. This paper presents a hybrid method that combines image segmentation, threshold techniques, and a hybrid KNN-CNN algorithm to enhance lung cancer image detection. The study examines existing segmentation and machine learning methods, proposes a novel algorithm, and validates its performance using benchmarks. The results demonstrate improved accuracy, sensitivity, and computational efficiency compared to existing approaches.