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.
Materials and 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 .
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%.
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.