Research Article
A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images
Table 5
Segmentation performance of the proposed liver tumor segmentation method on three datasets.
| | VOE | RVD | ASD | RMSD | MSD |
| Hospital data | | | | | | Mean | 15.52 | 9.02 | 1.87 | 2.50 | 7.55 | SD | 7.01 | 6.96 | 0.97 | 1.18 | 3.71 | Worst | 38.46 | 26.56 | 6.43 | 7.11 | 17.00 | Best | 3.91 | 0 | 0.54 | 0.73 | 1.41 | MIDAS | | | | | | Mean | 32.19 | 10.07 | 1.51 | 1.92 | 4.09 | SD | 11.13 | 28.00 | 0.41 | 0.45 | 1.43 | Worst | 86.96 | 93.55 | 2.97 | 3.85 | 10.94 | Best | 15.29 | 0 | 0.68 | 1.1 | 1.76 | 3Dircadb | | | | | | Mean | 28.22 | -8.46 | 1.81 | 2.35 | 5.77 | SD | 11.90 | 18.45 | 1.28 | 1.70 | 4.61 | Worst | 64.52 | -63 | 6.77 | 9.03 | 25.64 | Best | 4.59 | 0 | 0.19 | 0.36 | 0.70 |
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