scholarly journals Constantinides et al. Signal to Noise Measurements in Magnitude Images from NMR Phased Arrays, Magn Reson Med 1997;38:852-857.

2004 ◽  
Vol 52 (1) ◽  
pp. 219-219 ◽  
Author(s):  
Chris D. Constantinides ◽  
Ergin Atalar ◽  
Elliot McVeigh
Keyword(s):  
Phased Arrays ◽  
Signal To Noise ◽  
Noise Measurements

scholarly journals Signal-to-noise measurements in magnitude images from NMR phased arrays

1997 ◽  
Vol 38 (5) ◽  
pp. 852-857 ◽  
Author(s):  
Chris D. Constantinides ◽  
Ergin Atalar ◽  
Elliot R. McVeigh
Keyword(s):  
Phased Arrays ◽  
Signal To Noise ◽  
Noise Measurements

Dynamic signal-to-noise measurements of textured optical storage media

1984 ◽  
Vol 23 (22) ◽  
pp. 3956 ◽  
Author(s):  
S. Y. Suh ◽  
D. A. Snyder ◽  
D. L. Anderson ◽  
H. G. Craighead
Keyword(s):  
Optical Storage ◽  
Signal To Noise ◽  
Storage Media ◽  
Noise Measurements ◽  
Dynamic Signal

scholarly journals Signal to Noise Ratio as a Cross-Platform Metric for Intraoperative Fluorescence Imaging

2020 ◽  
Vol 19 ◽  
pp. 153601212091369
Author(s):  
Asmaysinh Gharia ◽  
Efthymios P. Papageorgiou ◽  
Simeon Giverts ◽  
Catherine Park ◽  
Mekhail Anwar
Keyword(s):  
Tumor Cells ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Size Variation ◽  
Pixel Size ◽  
Signal To Noise ◽  
Noise Sources ◽  
Noise Measurements ◽  
Noise Ratio ◽  
The Impact

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.

scholarly journals GNSS multipath detection using three-frequency signal-to-noise measurements

GPS Solutions ◽  
2015 ◽  
Vol 20 (3) ◽  
pp. 399-412 ◽  
Author(s):  
Philip R. R. Strode ◽  
Paul D. Groves
Keyword(s):  
Signal To Noise ◽  
Frequency Signal ◽  
Noise Measurements ◽  
Multipath Detection
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