A Novel Method for Forgery Detection on Lung Cancer Images

Abstract

With the increase in lung cancer cases in recent years, rapid advances have been made in imaging technologies for lung cancer detection. Thanks to these advances in image processing and medicine, more successful disease diagnosis is achieved. On the other hand, the security of these images is one of the issues that are overlooked or little thought about in this field. The security of images such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) is as important as disease detection. Manipulations such as cyber attacks, commit insurance forensic and destruction of evidence can be carried out on health images for various purposes. This problem is included in the study area of both image processing and information security. In this study, we developed a new image forgery detection method based on Center Symmetric Local Binary Pattern texture extraction algorithm, which has not been used on lung cancer images before as far as we known. We tested this method that we have developed on a very up-to-date lung cancer image data set. Although the success of the method is the first study, it is satisfactory. The experimental results of the proposed method show that our method can be used in this field.

Keywords

• information security
• lung cancer images
• computed tomography
• passive image security.

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