Résumé
Medical image processing aims to help the doctors to improve the diagnosis process. Computed Tomography (CT) Scanner is an imaging medical device used to create cross-sectional 3D images of any part of the human body. Today, it is very important to secure medical images during their transmission, storage, visualization and sharing between several doctors. For example, in image forensics, a current problem consists of being able to identify an acquisition system from only digital images. In this thesis, we present one of the first analysis of CT-Scanner identification problem. We based on the camera identification methods to propose a solution for such kind of problem. It is based on extracting a sensor noise fingerprint of the CT-Scanner device. The objective then is to detect its presence in any new tested image. To extract the noise, we used a wavelet-based Wiener denoising filter. Then, we depend on the properties of medical images to propose advanced solutions for CT-Scanner identification. These solutions are based on new conceptions in the medical device fingerprint that are the three dimension fingerprint and the three layers one. To validate our work, we applied our experiments on multiple real data images of multiple CT-Scanner devices. Finally, our methods that are robust, give high identification accuracy. We were able to identify the acquisition CT-Scanner device and the acquisition axis.