Internal validation
gain, EDH, IVH
The comparison of Dice scores between 4-class automatic segmentations (CNN1 and CNN2) and the 4-class manual segmentation is displayed on Fig. Barplots of the DICE scores (mean and standard error) computed on each lesion and on overall lesions between automatic and manual segmentations on the test sub-dataset of Dataset1 (6 patients—17 CT-scans). Upper part shows the comparison of CNN1 and CNN2, as well as an illustration of the resulting lesions. Lower part shows the comparison of CNN3 and CNN4, as well as an illustration of the resulting lesions. Significance was assessed with non-parametric two-side Wilcoxon tests. *p < 0.05.On every lesion, CNN2 (average DICE score on overall lesions = 0.63), showed statistically significantly better results than CNN1 (BLAST-CT) (0.34). The gain is particularly large on Od and IVH lesions, where CNN1 performs poorly.The comparison of Dice scores between 7-class automatic segmentations (CNN3 and CNN4) and the 7-class manual segmentation are displayed on Fig. On the overall lesion, CNN4 (average DICE score on overall lesions = 0.64), showed statistically significantly better results than CNN3 (0.55). On the EDH lesion, results are unexpected, as CNN3 is better than CNN4, but not significatively, probably due to the small sample size of images containing this lesion.