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Comparative Analysis of Low-Rank Matrix Denoising Algorithm-Based MRI and CT Images in Diagnosis of Cerebral Aneurysms
Scientific Programming Pub Date : 2021-07-15 , DOI: 10.1155/2021/2480037
Aijun Li 1 , Yuehua Zheng 1 , Yan Li 2 , Tao Zhou 1 , Peicheng Cao 1 , Shaobo Qiu 1 , Jinpeng Wang 1
Affiliation  

This study aimed to compare the role of magnetic resonance imaging (MRI) and computed tomography (CT) images based on the low-rank matrix (LRM) denoising (LRMD) algorithm in the diagnosis of cerebral aneurysms (CAs). By comparing the role of MRI and CT in the diagnosis of CA, it would be helpful to formulate more reasonable diagnosis strategies and provide a solid foundation for clinical treatment of patients. 80 patients with cerebral aneurysm admitted to hospital were selected as the research objects. First, the LRMD algorithm was established and applied to the image denoising process of MRI and CT. Then, the diagnosis rate of CA by MRI and CT before and after denoising was compared, and the diagnostic rates of the two methods for aneurysms of different sizes were compared. Finally, the location, foci, and patient satisfaction of the aneurysm were compared. The results showed that the MRI and CT images after denoising with LRM were clearer, and the secondary structures in the brain were more obvious. It meant that LRMD had good image denoising effect. The diagnostic rate of denoised MRI and CT was improved. Although the difference was not statistically notable, the diagnostic rate of CT was obviously higher in contrast to MRI (). The diagnostic rate of CT for smaller aneurysms (<3 mm and 3–5 mm) was also notably higher in contrast to MRI (). However, there was no difference in the diagnosis of tumor location between the two. The clarity of CT diagnostic images was better than MRI (). Accordingly, patients were more satisfied with CT in contrast to MRI (). In summary, CT images based on the LRMD algorithm were superior to MRI in the diagnosis of CA, and it could provide more accurate diagnosis results.

中文翻译:

基于低秩矩阵去噪算法的MRI和CT图像在脑动脉瘤诊断中的对比分析

本研究旨在比较磁共振成像 (MRI) 和基于低秩矩阵 (LRM) 去噪 (LRMD) 算法的计算机断层扫描 (CT) 图像在脑动脉瘤 (CA) 诊断中的作用。通过比较MRI和CT在CA诊断中的作用,有助于制定更合理的诊断策略,为患者的临床治疗提供坚实的基础。选取住院脑动脉瘤患者80例作为研究对象。首先,建立了LRMD算法并将其应用于MRI和CT的图像去噪过程。然后比较去噪前后MRI和CT对CA的诊断率,比较两种方法对不同大小动脉瘤的诊断率。最后,位置,焦点,和患者对动脉瘤的满意度进行了比较。结果表明,LRM去噪后的MRI和CT图像更清晰,脑内二级结构更明显。这意味着LRMD具有良好的图像去噪效果。提高了去噪MRI和CT的诊断率。尽管差异无统计学意义,但 CT 的诊断率明显高于 MRI。)。与 MRI 相比,CT 对较小动脉瘤(<3 毫米和 3-5 毫米)的诊断率也明显更高。)。然而,两者在肿瘤位置的诊断上没有差异。CT诊断图像的清晰度优于MRI()。因此,与 MRI 相比,患者对 CT 的满意度更高()。综上所述,基于LRMD算法的CT图像对CA的诊断优于MRI,可以提供更准确的诊断结果。
更新日期:2021-07-15
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