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The slope of each regression line was calculated.
Bladder wall thickness (red line) was calculated to be ~1.00 mm or approximately 17 pixels.
The correlation constant for the fitted line was calculated to beR2 = 0.9833 and 0.9797 for RB5 and RO4, respectively.
The line was calculated from the generalized Pareto distribution (GPD) formula, and the circles were calculated from the original dataset.
The regression line was calculated using the least square statistical method and was found to be (r = 0.999).
Theoretical travel time curve assuming a hypocenter depth of 14 km (orange line) was calculated from the 1D velocity structure model of Ukawa et al. (1984).
For each of the seven heterogeneity levels, a regression line was calculated between the perfusion defect level and the parameter of the algorithm studied (Figure 3B).
The plasma concentration (solid line) was calculated by applying the plasma partitioning coefficient and metabolite correction to the scaled whole-blood activity.
The regression line was calculated as Y = mX + c, where X was the concentration of standard and Y was the response (peak area expressed as AU).
The median inhibitory concentration (IC50) of erlotinib for cell growth of each cell line was calculated using GraphPad Prism 5.0 software.
For each algorithm, a diffuse heterogeneity discrimination power (HDP) was obtained as follows: for each level of the six TP perfusion defect, a regression line was calculated between the heterogeneity level and the parameter of the algorithm studied (Figure 3A).
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