Detection of Lung Cancer Using Binarization Technique

The IUP Journal of Information Technology, Vol. XIII, No. 4, December 2017, pp. 7-19

Posted: 10 Aug 2018

Date Written: December 26, 2017

Abstract

Nowadays, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, and the time factor is very important to detect the abnormality issues in target images, especially in various cancer tumors such as lung cancer and brain cancer. The proposed system consists of five basic stages. In the first stage, CT lung image affected with cancer is taken. In the second stage, enhancement technique is applied to get the best level of quality and clarity. In the third stage, segmentation algorithm is applied, and in the next stage, morphological operations erosion and dilation are used to smooth the boundaries of the lung. Finally, in the last stage, feature extraction is applied to obtain the general features from enhanced segmented image which gives indicators of normality or abnormality of image. Simulations are carried out on various lung CT images and are also compared with the existing methods. The superiority of the proposed method is presented and justified. The proposed method gives very promising results of various quality metrics like accuracy, sensitivity, specificity and various other image quality metrics.

Keywords: Cancer Tumors, Enhancement, Segmentation, Morphological Operations, Feature Extraction

Suggested Citation

Mahalaxmi, G and Tirupal, T, Detection of Lung Cancer Using Binarization Technique (December 26, 2017). The IUP Journal of Information Technology, Vol. XIII, No. 4, December 2017, pp. 7-19, Available at SSRN: https://ssrn.com/abstract=3220305

G Mahalaxmi (Contact Author)

GPCET ( email )

Kurnool
Andhra Pradesh
India

T Tirupal

GPCET ( email )

Kurnool
Andhra Pradesh
India

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