An Analysis of Lung Tumor Classification Using SVM and ANN with GLCM Features

Abstract

Lung cancer is dangerous when it comes to life of humans and it happened by growth of abnormal cells in lungs. Due to metastasis in closed tissues, it can be spread in other parts of the body. For detection and segmentation of tumors, various image processing methods are in use which can identify the tumor at different stages. Our proposed solution suggests to use k-means and EK-means clustering methods on various images of tumors where features are extracted by geometrical features and training is done by advance machine learning algorithms like artificial neural networks (ANN) and support vector machine (SVM) where it classifies the tumor into benign or malignant type and provides tumorous part as a result of segmentation. We have done feature extraction by further segmenting GLCM features into Haralick features and this is our achievement.