Sahand Shahalinejad, Atefeh Bahador, Ali Niapour,
Volume 12, Issue 1 (11-2022)
Abstract
Background and Aim: Noise reduction in medical images is important. Excessive distortion in medical images reduces the accuracy of diagnosis of various diseases or structures. Violet conversion and filtering are among the most widely used methods for reducing noise in medical images. The aim of this study was to compare noise reduction using filtration (low-pass, mid-pass, and high-pass filters) as well as violet conversion from MRI images.
Methods: In this study, using MATLAB software, noisy MRI data were entered into the program environment and each of the proposed algorithms including filtering (low-pass, mid-pass, and high-pass filters) as well as violet conversion were implemented separately on images. And the ideal output was obtained due to the nature of the noise.
Results: The results obtained from the proposed violet and filtering methods were compared and analyzed. The signal-to-noise ratio (SNR) of all filters used and the violet conversion displayed a value above 30 dB. Violet conversion for selected images has a higher SNR value, and in some images, this difference is more than 40 dB. According to the images and relative PSNR values, among all the studied methods, the best dehumidification is when the CWT method was used. In this case, the PSNR is high and there is the most similarity between the degenerate image and the original image.
