Table 7.

Brain tumor segmentation results.

Model	Accuracy (%0)	Recall (%)	Specificity (%)	F-measure	Dice (%)	IoU (%)
U-Net (No Augmentation)	99.66	87.16	99.98	0.93	80.2 ± 0.36	72.9 ± 0.40
LBP	98.16	59.08	99.72	0.71	78.0 ± 0.40	70.6 ± 0.44
GLCM	99.73	65.00	99.00	0.75	75.9 ± 0.43	68.3 ± 0.47
Transfer learning	99.13	76.56	99.76	0.83	73.7 ± 0.46	65.9 ± 0.49

Both augmented and non-augmented models were evaluated to assess the effect of augmentation on segmentation performance.