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Method and System of Multivariate Analysis on Volume-Wise Data of Reference Structure Normalized Images for Improved Quality in Positron Emission Tomography Studies

机译:正电子发射层析成像研究中参考结构归一化图像体积明智数据的多变量分析方法和系统,以提高质量

摘要

A method and system are provided to mask out the background in dynamic PET images, to perform pre-normalization on the masked dynamic PET images, and to apply multivariate image analysis (e.g., principal component analysis PCA) on the masked pre-normalized dynamic PET images in order to improve the quality of the dynamic PET images and the PET study. A masking operation applies PCA to untreated dynamic PEET images before any pre-normalization in order to mask out the background pixels. This masking operation uses the Otsu method. A first normalization method is background noise pre-normalization where pixel values are corrected for background noise. A second normalization method is kinetic pre-normalization where the contrast within an image is improved. Multivariate analysis such as PCA may be applied on the whole volume to find the largest variance in the structure.
机译:提供了一种方法和系统,以掩盖动态PET图像中的背景,对掩盖的动态PET图像执行预归一化,以及在掩蔽的预归一化的动态PET上应用多元图像分析(例如,主成分分析PCA)为了提高动态PET图像和PET研究的质量。遮罩操作在进行任何预规范化之前将PCA应用于未经处理的动态PEET图像,以遮罩背景像素。此掩蔽操作使用Otsu方法。第一种归一化方法是背景噪声预归一化,其中针对背景噪声校正像素值。第二种归一化方法是动态预归一化,其中图像内的对比度得到改善。多变量分析(例如PCA)可应用于整个体积,以发现结构中的最大差异。

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