Feature extraction for lesion margin characteristic classification from CT Scan lungs image

Abstract

Lung cancer is one of the common cancer which occurred in both male and female. Revealed by WHO data, in 2012, this disease become one of the major cause of death in worldwide with the mortality rate about 1.59 million. An early detection of lung cancer by using Computed Tomography (CT) Scan can provide more opportunity to survive. However, the diagnosis of lung cancer by reading the CT scan image which performed by radiologists may lead to an error. A computer-based digital image processing is a solution to improve the accuracy and consistency in reading the CT Scan image result. This study aim is to identify the morphological characteristic of regular and irregular margins by using feature extraction method. In this research, image processing divided into several stages refer to the segmentation process with Otsu method, feature extraction with number of features such as convexity, solidity, circularity, and compactness, and the last is classification by using Multi Layer Perceptron (MLP). The classification process of features convexity, solidity, circularity, and compactness, resulted in the accuracy value of 85%, sensitivity of 85%, and specificity of 85%.