A statistical approach for MR and CT images comparison

resonance (MR) and computed tomography (CT) images in order to obtain a more accurate diagnostics. This is rather complex when the images under test have very different noise level. In this paper, a technique to compare the quality of the CT and MR images is introduced. The proposed technique is useful to assess the effect of different noise distribution on medical images and to equalize the examinations produced by different imagining technologies in terms of clearness of images and sharpness of contours. The authors, after examining the statistical properties of the noise affecting CT and MR images, analyze its effect on final image quality. Then, a methodology to compare the mean square errors relevant to CT and MR images is proposed. The study was carried out using images obtained from patients under neuropsychological test. The experimental tests have been performed by corrupting the original data with different noise levels.