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Table 2 Results of the comparison of the proposed method with other segmentation methods from the literature

From: Modified distance regularized level set evolution for brain ventricles segmentation

Methods Sensitivity Specificity Accuracy
Proposed method (atrophy CT, n = 20; normal CT, n = 20; atrophy MRI, n = 20; normal MRI, n = 20) 65%–90% 98%–99% 95%–98%
DRLSE (implemented) 74%–79% 91%–93% 92%–94%
Region based level set (MRI, n = 124) [38] 84%–89% 96%–97%
DRLSE and deep structure (MRI, n = 45) [39] 84%–95%
Fuzzy and evidential reasoning (MRI, n = 17) [40] 55%–90% 60%–80%
Hybrid genetic and EM algorithm (MRI, n = 10) [41] 45%–85%
Bayesian morphometry (MRI, n = 95) [42] 60%–80% 30%–60%
EGS-SOM (MRI, n = 57) [43] 76%–80% 95%–96%
HFS-SOM (MRI, n = 57) [43] 66%–77% 80%–85%