Research on Denoising of Brain MRI of Alzheimer's Disease Based on BM3D Algorithm

Abstract

Alzheimer's disease is a chronic degenerative disease of the acquired nervous system. Early detection and early treatment are particularly important. According to the technical requirements of brain magnetic imaging, the important step before brain magnetic imaging segmentation is image preprocessing and image denoising, which can more accurately segment the effective lesion features of magnetic imaging through image recognition. The algorithm studied in this paper is the BM3D method of image preprocessing and denoising. The BM3D noise algorithm model is a non-local denoising method, which is a spatial algorithm, and the other transform method is a conversion algorithm, which has a significant denoising effect. The image is grouped by two similar blocks through the BM3D algorithm and then collaboratively filtered and aggregated. The experimental analysis shows that the image processed by the BM3D algorithm is significantly better than the original image, and it can solve the problem of noise in the image and blurring of the boundary between the tissues.