Denoising of Degenerative Lumbar Spine Lesions MRI Images Using Block-Matching and 3D Filtering

Yongzhao Zhang,Jianshi Yin,Jun Liu,Junsheng Wang,Han Yan,M Pallikonda Rajasekaran

doi:10.1155/2021/2430380

Yongzhao Zhang, Jianshi Yin + Show 4 more

Open Access

https://doi.org/10.1155/2021/2430380

Copy DOI

Abstract

This work was aimed to explore the application of the L2-block-matching and 3-dimentional filtering (BM3D) (L2-BM3D) denoising algorithm in the treatment of lumbar degeneration with long- and short-segment fixation of posterior decompression. 120 patients with degenerative lumbar scoliosis were randomly divided into group A (MRI images were not processed), group B (MRI images were processed by the BM3D denoising algorithm), and group C (MRI images were processed by the BM3D denoising algorithm based on weighted norm L2). This denoising algorithm was comprehensively evaluated in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and running time. Besides, the results of surgeries based on different denoising methods were assessed through the surgical time, intraoperative blood loss, postoperative drainage, and postoperative follow-up. The results showed the following: (1) PSNR (peak signal-to-noise ratio) and SSIM (structural similarity index measure) of the L2-BM3D algorithm are better than those of the BM3D algorithm (31.21 dB versus 29.33 dB, 0.83 versus 0.72), while mean square error (MSE) was less than that of the BM3D algorithm ( P < 0.05 ). (2) The operation time, intraoperative bleeding, and postoperative drainage volume in group C were lower than those in group B and group A ( P < 0.05 ). The postoperative follow-up results showed that, in group C, the postoperative VAS (visual analysis scale) score (1.03 ± 0.29) and ODI (Oswestry disability index) (9.29 ± 0.32) were lower, indicating that the postoperative recovery effect of patients was better. Therefore, the patient’s postoperative recovery effect was better. In conclusion, the L2-BM3D algorithm had an ideal denoising effect on MRI images of lumbar degeneration and was worthy of clinical promotion.

Highlights

Studies suggested that degenerative lumbar lesions were one of the main causes of low back pain
In order to investigate the application of different denoising algorithms for processing MRI medical images in the treatment of lumbar degeneration with long- and shortsegment fixation after decompression, the block-matching and 3-dimentional filtering (BM3D) denoising algorithm was improved in this study to propose the image block similarity calculation method L2-BM3D based on weighted norm L2. en, the L2-BM3D denoising algorithm was adopted to analyze the denoising effect and clinical surgery effect, which were compared with those of the BM3D denoising algorithm
With the help of mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and running time, the denoising algorithm was evaluated to help verify the advantages of the L2-BM3D denoising algorithm

Summary

Introduction

Studies suggested that degenerative lumbar lesions were one of the main causes of low back pain. Surgery is the main method for the treatment of degenerative lumbar scoliosis, including osteotomy, posterior decompression, and internal fixation [6]. The clinical examination methods for degenerative lumbar scoliosis include X-ray, computed tomography (CT), radionuclide imaging, and MRI [10]. In this study, the BM3D denoising algorithm will be used based on weighted L2 norm to process MRI images and for disease diagnosis of degenerative lumbar scoliosis patients. E application value of the algorithm will be evaluated by observing the treatment effect of this method in the diagnosis of degenerative lumbar scoliosis patients, so as to provide more research basis for clinical patients to obtain more effective diagnosis and treatment methods In this study, the BM3D denoising algorithm will be used based on weighted L2 norm to process MRI images and for disease diagnosis of degenerative lumbar scoliosis patients. e application value of the algorithm will be evaluated by observing the treatment effect of this method in the diagnosis of degenerative lumbar scoliosis patients, so as to provide more research basis for clinical patients to obtain more effective diagnosis and treatment methods

Materials and Methods

Experimental Results

Discussion