Reducing noise in medical MRI images using the Atangana-Baleanu fractional operator

Анотація

This work examines fractal differential operators and their usage in processing medical MRI images, focusing on the Atangana-Baleanu fractial operator. Numerical approximations of this operator are reviewed and describes how the approximation coefficients are calculated. Using these approximations, directionally oriented masks are created for image denoising, that are integrated into a custom algorithm and software to enhance image quality. A visual and analytical comparison is made between denoised and original images, and the results are compared against both fractal-based and traditional denoising methods. The study concludes with insights into the effectiveness of the Atangana-Baleanu fractal operator for MRI image processing.

Посилання

[1] Behzad Ghanbari, Abdon Atangana, A new application of fractional Atangana– Baleanu derivatives: Designing ABC-fractional masks in image processing, Physica A: Statistical Mechanics and its Applications, Volume 542, 2020, 123516, ISSN 0378-4371, https://doi.org/10.1016/j.physa.2019.123516.
[2] Ghanbari, Behzad & Atangana, Abdon. (2020). Some new edge detecting techniques based on fractional derivatives with non-local and non-singular kernels. Advances in Difference Equations. 2020. 10.1186/s13662-020-02890-9
[3] Li, C., Zeng, F.: The finite difference methods for fractional ordinary differential equations. Numer. Funct. Anal. Optim.34(2), 149–179 (2013)
Опубліковано
2025-11-13
Як цитувати
Bereziuk, V., & Sokolovskyy, Y. (2025). Reducing noise in medical MRI images using the Atangana-Baleanu fractional operator. Комп’ютерне моделювання та інформаційні технології. вилучено із https://conf.nltu.edu.ua/index.php/conf1/article/view/289
Номер
2024: Комп’ютерне моделювання та інформаційні технології
Розділ
МАТЕМАТИЧНЕ І ПРОГРАМНЕ ЗАБЕЗПЕЧЕННЯ
Creative Commons License

Ця робота ліцензується відповідно до Creative Commons Attribution 4.0 International License.