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Image luminosity features and similarity measures were determined using the EyeOpen image library for C# [15].
Optimal cutting parameters for each performance measure were obtained; also the relationship between the parameters and the performance measures were determined using multiple linear regression.
In this study, four substitute groups with variable geometric features but constant porosity were scanned using micro-computed tomography (μCT) and their geometric measures were determined using an advanced image-processing algorithm based on fuzzy distance transform and new pore size definition.
Anthropometric measures were determined using standard procedures.
All final assessment measures were determined using last observation carried forward (LOCF).
Correlations between distance measures were determined using Mantel tests and considered significant at P < 0.05 after 9999 randomizations.
Similar(52)
The statistical significance of these measures was determined using permutation testing (n = 1000 permutations).
The relationship of urinary NOx to disease measures was determined using a Spearman correlation coefficient.
The test retest reliability of each measure was determined using two baseline measurements performed before exercise by an interclass correlation coefficient (R) and coefficient of variation (CV).
Background was subtracted from each measurement as follows; the mean intensity of a region on the substratum adjacent to each neuron measured was determined using the same region of interest as used for the measurement on the neuron and was subtracted from the measurement obtained from the neuron.
The P value for the primary outcome measure was determined using a two-tailed test.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com