Master’s Thesis Discusses Medical Image Denoising Using Hybrid Algorithms

The Electrical Engineering Department at the University of Technology awarded a master’s degree to researcher Kholoud Nasser Hussein for her thesis titled Medical Images Denoising Based on Hybrid Genetic and Bat Algorithm.
The research proposed a novel hybrid algorithm combining genetic and bat-inspired approaches to reduce noise in medical images, enhancing their peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The study involved analyzing various medical imaging modalities such as MRI, CT scans, X-rays, and ultrasounds.
The discussion committee was chaired by Dr. Yusra Hussein Ali and included faculty members and supervisors.