Improving Grayscale Medical Images (X-Rays, MRI, CT Scans)

Medical images provide critical information that physicians need to diagnose a condition and make appropriate treatment decisions. The diagnostic process relies heavily on human perception. Unfortunately, the potential for perceptual errors is unacceptable, impacting patients' lives. Therefore, image enhancement represents a crucial step in supporting medical diagnosis by improving its quality. In this research, we applied a new algorithm to enhance X-ray, MRI, and CT images. This algorithm aims to improve contrast and sharpness based on an empirical equation using trigonometric functions (cos) based on Fourier transforms and changing the value of one of its main parameters. Nasal polyps were more clearly identified in X-rays, and brain tumours were more clearly identified in MRI and CT scans. Histograms were used before and after enhancement, and we observed a significant difference between the original and enhanced images in terms of the histogram shift toward unity, demonstrating the success of this algorithm in improving contrast and organ prominence.