目的:SVDsketch[实现随机奇异值分解(rSVD)算法的MATLAB函数]使用容差(tol)自适应地确定矩阵草图逼近的秩。随着托尔越来越大,在矩阵草图中使用了较少的输入图像矩阵特征。这项研究的目的是优化压缩tol-99m(Tc-99m)L的值,L,亚乙基二半胱氨酸(LLEC)肾脏动态(RD)研究在最短时间内保留临床信息。
方法:在tol[0.00012(默认值)的不同值下,0.1、0.01和0.05]50Tc-99mLLECRD研究被压缩。两位核医学(NM)医生将tol=0.1的压缩图像与其输入图像进行了比较。计算每个研究的SVD计算时间和压缩因子。图像质量度量:错误,用于测量图像质量的结构相似性指标,亮度,全局对比因子(GCF),每像素对比度(CPP),和模糊用于图像质量的客观评估。计算了从压缩图像和原始图像估计的分割函数中的百分比误差。应用Wilcoxon符号秩检验发现肾脏分裂功能之间有统计学意义的差异,blur,GCF,CPP,以及压缩图像和原始图像的亮度。
结果:根据NM医生,tol=0.1的压缩图像与原始图像相同。基于图像质量度量,压缩图像的噪声明显减少,更亮,并且与输入图像相比具有更好的对比度。从tol=0.1的压缩RD研究和其原始研究估计的分裂肾功能差异无统计学意义。发现每个研究的SVD计算和压缩百分比为0.04725s,最高为74.53%。
OBJECTIVE: The SVDsketch [MATLAB function which implements a randomized singular value decomposition (rSVD) algorithm] uses tolerance (tol) to adaptively determine the rank of the matrix sketch approximation. As the tol gets larger, fewer features of input image matrix are used in the matrix sketch. The objective of this
study was to optimize the value of tol for compressing technetium-99m (Tc-99m) L,L, ethylenedicysteine (LLEC) renal dynamic (RD)
study in minimum time preserving clinical information.
METHODS: At different values of tol [0.00012(default), 0.1, 0.01, and 0.05] 50 Tc-99m LLEC RD studies were compressed. Two nuclear medicine (NM) physicians compared compressed images at tol = 0.1 with its input images. The SVD computation time and compression factor were calculated for each
study. The image quality metrics: Error, structural similarity index for measuring image quality, brightness, global contrast factor (GCF), contrast per pixel (CPP), and blur were used for objective assessment of image quality. Percentage error in split function estimated from compressed and original images was calculated. Wilcoxon signed-rank test was applied to find statistically significant difference between renal split function, blur, GCF, CPP, and brightness of the compressed image and the original image at .
RESULTS: As per NM physicians, compressed images estimated with tol = 0.1 were identical to the original images. Based on image quality metrics, compressed images were significantly less noisy, brighter, and have better contrast compared with its input images. There was insignificant difference in split renal function estimated from compressed RD
study at tol = 0.1 and its original
study. The SVD computation and percentage compression per study were found to be 0.04725 s and up to 74.53%.
CONCLUSIONS: The optimized value of tol for compressing Tc-99m LLEC RD study preserving clinical information was found to be 0.1, and SVD computation time: 0.04725 s.