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. 2021 Jul 26;11:69. doi: 10.1186/s13550-021-00810-w

Table 3.

Correlation coefficients (ϱ) between the distance metrics and the intensity-based (dis)similarity parameters (calculated in three different manners: α, β, γ; see details in the text)

Masking (dis)similarity parameter
Pearson (s) MI (s) NMI (s) HKL (d) L1norm (d) L2norm2 (d)
α 0.15 0.02 0.02 − 0.07 0.25 0.22
β 0.38 0.56 0.5 0.45 − 0.04 − 0.09
γ 0.4 0.6 0.51 − 0.02 0.07 0.09

MI mutual information, NMI normalised mutual information, HKL Kullback–Leibler divergence, L1Norm L1 norm or Manhattan norm, L2norm2 square L2 norm or square Euclidean distance, (s) similarity parameter, (d) dissimilarity parameter (data are rounded to two significant digits, the highest correlation coefficient is emphasized in bold text)