Medical imaging is a complicated procedure and acquired images are with intrinsic characteristics. As a tool to quantify the image quality, signal-to-noise ratio (SNR) is widely accepted by physicians in clinical situations. It is defined as the quotient of the mean signal intensity in a tissue region of interest and the standard deviation of the signal intensity in a region outside the anatomy of the object imaged. However, insufficient knowledge on its consistency with respect to different observers and tissue regions is known. In this paper, the consistency is studied with 324 simulated MR images of human brain. The consistency of SNR is validated between two observers and between tissues of white matter and cerebral spinal fluid. For the same type of tissues in each modality, Wilcoxon rank sum test suggests no significant difference between two observers(P＞0.70). For the same modality and observer, SNR between tissues correlates well (Pearson correlation coefficient rp＞0.71(P＜10－5), and Spearman’s rank correlation coefficient rs＞0.97(P＜10－3). This study indicates that SNR is consistent and robust regarding to different observers and tissues in objective quality assessment of magnetic resonance images. Further research will be carried on clinical images for objective assessment.
DAI Guangzhe, WANG Zhaoyang, CHEN Qian, YU Shaode, XIE Yaoqin. A Consistency Evaluation of Signal-to-Noise Ratio in Medical Image Quality Assessment: A Simulation Study on Human Brain Magnetic Resonance Images[J]. Journal of Integration Technology,2017,6(2):41-48Copy