Abstract
This article presents the research of texture enhancement algorithms on medical images. Medical MRI brain scans contain large areas with low level grey colors that carry useful information for doctors. Texture improvement allow to highlight large grey areas on images for future detailed recognition. Based on the study of existing texture enhancement methods, it was determined that fractal operators are effective for processing medical images. The mathematical framework of fractal operators is presented based on the approximation equation of the Grünwald-Letnikov fractional derivatives. The creation of fractal differential masks and the algorithm of masks usage for image enhancement are described based on this equation. The approximation error of the Grunwald-Letnikov derivative is calculated in comparison with the analytical value of the Grunwald-Letnikov derivative. The algorithm based on the fractal derivative shows improvements in image parameters such as contrast, correlation, energy, and homogeneity compared to the original image parameters. A comparison of the results of the algorithm based on the fractal differential with other algorithms for improving the texture of images is also given. It is concluded that the fractal differential algorithm is well-suited for MRI image enhancement tasks, unlike other algorithms, both in visual comparisons and numerical metrics, and thus can be applied to solve real-world problems.
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