利用PSNR和SSIM确定MR图像不对称系数的新模型

Muhammet Üsame Öziç, Seral Özşen
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引用次数: 5

摘要

人类的大脑由左右两个半球组成。这两个半球几乎是对称的,但不是完全对称。然而,在神经系统疾病中,大脑的体积损失开始在两个半球之间不对称地恶化。这种恶化可能是局部的,也可能是整个大脑的。对称性退化可作为神经系统疾病早期诊断及后续诊断的生物标志物。然而,有人指出,用数值方法分析大脑的不对称性是有问题的。本研究提出了一种新的脑对称性退化的数值分析方法。为了对磁共振图像进行不对称分析,必须通过寻找中矢状面来分离两个半球,即已知的对称轴。PSNR和SSIM系数通常用于两幅图像之间的质量测量。在研究中,对这些系数进行了不对称测量。通过确定OASIS数据库中70张对照和70张阿尔茨海默病MR图像的PSNR-SSIM系数进行统计分析。我们确定在MR图像的不对称性分析中使用PSNR和SSIM系数给出了有意义的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new model to determine asymmetry coefficients on MR images using PSNR and SSIM
The human brain consists of two hemispheres, right and left. These two hemispheres are almost symmetrical, not perfectly. However, in neurological diseases, the volumetric losses in the brain begin to deteriorate asymmetrically between the two hemispheres. This deterioration can be local or global in the brain. Symmetry deterioration can be a biomarker in the early stage diagnosis and the following of neurological diseases. However, it has been stated that the analysis of asymmetry in the brain by numerical methods is problematic. In this study, a new approach is proposed to analyze the brain symmetry deterioration numerically. In order to perform asymmetry analysis in MR images, two hemispheres must be separated from each other by finding the midsagittal plane which are known symmetry axis. The PSNR and SSIM coefficients are often used for quality measurements between two images. In the study, these coefficients were tested for asymmetry measurement. Statistical analysis was performed by determining PSNR-SSIM coefficients between 70 Control and 70 Alzheimer Disease MR images from the OASIS database. It was determined that the use of PSNR and SSIM coefficients in the asymmetry analysis of MR images gave meaningful results.
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