Joint Dense Residual and Recurrent Attention Network for DCE-MRI Breast Tumor Segmentation

Table 2

Comparison of experimental results of the different prediction models on the test set. All values in this table are averages from 32 test cases.

Method	Jaccard	DSC	SEN	SPE	PPV	HD
U-net [8]	0.6348	0.7557	0.8018	0.9989	0.7688	33.2948
Attention U-Net [22]	0.6386	0.7594	0.8013	0.9990	0.7787	19.5235
Residual U-Net [20]	0.6322	0.7555	0.8220	0.9988	0.7526	25.1890
Dense U-Net [21]	0.6529	0.7667	0.8031	0.9991	0.7781	20.9375
V-net [25]	0.6360	0.7587	0.8184	0.9989	0.7559	43.3051
Present model	0.6649	0.7827	0.8296	0.9990	0.7928	17.0818

The best results for the segmentation metrics in the comparison experiment are shown in bold.