Medical image noise reduction using Radon transform and Walsh list in Laplacian pyramid domain

Abstract

It is well known that noise on medical image resulting in low image quality has largely limited the diagnostic usefulness. Therefore, noise reduction for medical images is significantly urgent. However, most reported noise reduction methods, which are usually based on the local statistics of a medical image, are not efficient for medical image noise reduction. This Paper presents a novel approach for medical image noise reduction using Radon transform (RT) and an adaptive median filter based on Walsh list in the Laplacian pyramid domain. After that, experiments results on artificial and clinical X-ray Computed Tomography (CT) images with Gaussian noise and salt&pepper noise using proposed method and traditional methods have been summarized. Also, speckle reduction on Ultrasound (US) image has been performed using artificial US image. Based on the experimental results, it is concluded that the proposed method showed better capability for noise reduction on medical images compared with other traditional methods.

Cat Swarm Optimization Based Functional Link Artificial Neural Network Filter for Gaussian Noise Removal from Computed Tomography Images

“…Next, the fitness values of all the candidate points are to be calculated and then assigned a similar probability to identical fitness function of the cats. Otherwise, calculate the selecting probability of each candidate point using (1). In this mode only best, maximum, and minimum fitness values are to be calculated and it can be further used in tracing mode or to solve optimization problems.…”

“…CT imaging can provide quality visual information regarding human tissues at a particular time. Presently, CT imaging is becoming an indispensable part of the medical treatment process [1,2]. CT images can be distorted at any stages, such as during acquisition, processing, compression, storage, transmission, and reproduction.…”

Efficient reconfigurable architectures for 3D medical image compression

“…Despite the fact that the software experimentation of image de-noising [77][78][79][80][81][82][83] has gained much effort from the research community, it is worth noting that very few effort in hardware implementation.…”

“…Noise reduction is very important, as various types of noise is generated by medical imaging equipment, consequently, limits the effectiveness of medical image diagnosis [80], [82]. …”

Medical image denoising on field programmable gate array using finite Radon transform

“…Noise reduction in medical imaging applications is very important, as various types of noises generated by medical imaging equipment, consequently, limit the effectiveness of medical image diagnosis [2].…”