R2AU-Net: Attention Recurrent Residual Convolutional Neural Network for Multimodal Medical Image Segmentation

Table 1

Performance comparison of R2AU-Net and other networks on the ISIC dataset.

Methods	F1-score	Sensitivity	Specificity	Accuracy	AUC
SegNet [19]	0.7092	0.8056	0.8147	0.8121	0.8101
U-Net [3]	0.6954	0.7160	0.8636	0.8216	0.7898
Attention U-Net [20]	0.7541	0.7627	0.8966	0.8585	0.8297
RU-Net [21]	0.679	0.792	0.928	0.880	0.8374
R2U-Net [21]	0.691	0.726	0.971	0.904	0.8565
Attention Res U-Net	0.8545	0.8363	0.9519	0.9190	0.8941
R2AU-Net	0.8660	0.8214	0.9699	0.9277	0.8957