The contrast was then calculated as the difference between node and background ROI mean count values, with noise being defined as the standard deviation in the background ROI for calculating the contrast to noise ratio (CNR) of the simulated SLN, as explained in detail elsewhere [37].
Figure 3c shows the mean measured versus true activity concentration in the 37 mm VOI in the warm background compartment of the phantom along the identity line, and Fig. 3d shows the percent deviation in this background activity concentration.
The signal-to-noise ratio (SNR) was determined as follows: SNR=frac{SIast sqrt{2}}{noise} where SI is the signal intensity in either the liver parenchyma and noise representing the standard deviation in the background (air) measured in the corner of the image outside areas of artefacts.
The (relative) mean percent standard deviations measured in background ROIs were 1.53, 1.05, and 1.00 for the gated, gating+, and ungated values, respectively.
The ΔSO2/ΔCO2 ratio was determined from the deviation from background in plumes.
A miRNA was considered detected if the spot intensity was at least two standard deviations above background in at least two of the samples.
Within Limma, prior to channel normalization, microarray outputs were filtered to remove spots of poor signal quality by excluding those data points with mean intensity less than two standard deviations above background in both channels.
However, it may be the only option in analyzing datasets where standard deviation of background signal is not given.
Blood SNR was calculated as the ratio of the average blood signal measured in the RV cavity to the standard deviation of background signals.
The background threshold value is set to be: average background counts + standard deviation of background counts * sigma_factor.
