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. 2020 Jul 2;21(8):987–997. doi: 10.3348/kjr.2020.0237

Table 3. Agreement of Volumetric Indices between Deep Learning Segmentation and Ground Truth Segmentation in Test Dataset-1.

Liver Volume Spleen Volume Liver/Spleen Volume Ratio
95% LOA* P 95% LOA* P 95% LOA* P
Total -0.17 ± 3.07 0.19 -0.56 ± 3.78 0.001 0.39 ± 4.89 0.06
Subgroups
 Healthy liver -0.42 ± 2.49 0.08 -0.97 ± 4.15 0.02 0.55 ± 5.30 0.28
 Fatty liver disease -0.33 ± 2.23 0.12 -0.77 ± 2.84 0.007 0.44 ± 3.04 0.13
 Non-cirrhotic chronic liver disease 0.12 ± 2.63 0.64 -0.14 ± 4.32 0.74 0.25 ± 4.95 0.59
 Liver cirrhosis -0.75 ± 3.58 0.03 0.06 ± 4.21 0.88 -0.81 ± 5.15 0.10
 Post-hepatectomy 0.55 ± 3.64 0.11 -0.99 ± 2.79 0.001 1.54 ± 4.82 0.002

*Data are Bland-Altman 95% LOA expressed in percentages as mean difference ± 1.96 × standard deviation of difference, p values for statistically significant difference in mean difference from zero. LOA = limits of agreement