Table 3

The agreement scores of each feature generated from segmentation results by all users, JSEG and the gold standard, assessed by ICC

FeaturesAll 7 physiciansGP 1 vs goldGP 2 vs goldGP 3 vs goldGP 4 vs goldJSEG vs gold
PC3*0.960.970.970.990.980.95
Variance blue channel*0.880.890.900.950.920.84
Variance blue channel†0.970.970.970.990.980.98
Compactness*0.570.520.570.700.640.13
Radial variance*0.630.670.600.750.580.29
Green–blue correlation*0.770.870.770.800.870.65
Green–grey correlation*0.800.880.820.880.870.66
PC3†0.980.980.970.990.990.95
Entropy red channel†0.900.940.890.950.900.93
Entropy red channel*0.920.960.900.970.940.86
Entropy blue channel†0.930.930.940.970.960.94
Entropy blue channel*0.880.930.880.940.900.82
GLRLM_HGRE_4Level†0.840.910.770.930.870.86
GLRLM_SRLGE_4Level†0.950.960.950.980.970.93
GLRLM_SRLGE_2Level†0.940.940.940.970.950.94
Tamura's coarseness features*0.940.930.930.970.950.91
Probability score0.910.910.900.940.930.48
  • Features are listed in order according to RFE ranking between 91 features in our previous study. All of the p values of each ICCs in this table are ≤0.01. The failure cases (34/347) of autosegmentation by JSEG are not included in the analysis.

  • *Derived from the lesion area only.

  • †Derived from the whole cropped image.

  • GLRLM, grey level run length matrix; GP, general practitioner; HGRE, high grey level run emphasis; ICC, intraclass correlation coefficient; PC3, the variance along the coordinates of the third principal components; RFE, recursive feature elimination; SRLGE, short run low grey level emphasis.