Research Article
3D Liver Tumor Segmentation in CT Images Using Improved Fuzzy C-Means and Graph Cuts
Table 2
Statistical performance of the proposed method compared to some other methods. Results are represented as mean ± standard deviation.
| Method | Year | Auto | Dataset | VOE (%) | RVD (%) | ASD (mm) | RMSD (mm) | MaxD (mm) | DICE | Runtime |
| Stawiaski et al. [14] | 2008 | Interactive | LTSC08 | 29.49 ± 12.80 | 23.87 ± 34.72 | 1.50 ± 0.67 | 2.07 ± 0.89 | 8.30 ± 4.10 | — | 5–8 mins | Li et al. [12] | 2012 | Semi | LTSC08 | 26.31 ± 5.79 | −10.64 ± 7.55 | 1.06 ± 0.38 | — | 8.66 ± 3.17 | — | 30 s | Kadoury et al. [17] | 2015 | Auto | LTSC08 | 25.2 ± 1.7 | 14.3 ± 2.8 | 1.4 ± 0.3 | 1.6 ± 0.4 | 6.9 ± 1.8 | — | 102 s | Moghbel et al. [10] | 2016 | Auto | 3Dircadb | 22.78 ± 12.15 | 8.59 ± 18.78 | — | — | — | 0.75 ± 0.15 | 30 s/slice | Foruzan and Chen [19] | 2016 | Semi | 3Dircadb | 30.61 ± 10.44 | 15.97 ± 12.04 | 4.18 ± 9.60 | 5.09 ± 10.71 | 12.55 ± 17.07 | 0.82 ± 0.07 | 154 s | Our method | | Semi | 3Dircadb | 29.04 ± 8.16 | −2.20 ± 15.88 | 0.72 ± 0.33 | 1.10 ± 0.49 | 4.25 ± 3.03 | 0.83 ± 0.06 | 45 s |
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