Table 7 Comparative analysis results for Features.

From: Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging

Metrics

NRAN

DSSE-V-Net

DenseUNet+

FSM-ICL

Precision

0.683

0.792

0.882

0.9543

Classifications (/Region)

0.621

0.749

0.826

0.9021

Error (%)

10.19

7.72

5.23

3.043

Classification Time (ms)

2001.27

1532.69

1014.07

570.365

Segmentation Accuracy (%)

62.59

73.02

83.45

91.487

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