Lung Cancer Detection using Local Energy-Based Shape Histogram (LESH) Feature Extraction Using Adaboost Machine Learning Techniques

Abstract

It is difficult to find the exact symptoms of lung cancer due to the formation of the majority of cancer tissues in which the large tissue structure intersects differently. With digital images, this question can be evaluated. Images with the basic operation of the LESH Algorithm will be examined in this strategy. GLCM approach is used in this paper to pre-process the snap shots and feature extraction system and to check a patient's disease rate at its it's premature or unnatural to know it. The cancer stage will be assessed with the aid of the results . Using the data set and the cancer patient's survival rate can be calculated. The conclusion is based entirely on the accurate and incorrect arrangement of tissue patterns.