most citedEAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT

17 citations · 17 across the 1 of their papers we have counts for

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1 paper

eess.IV2021★ 17 cited

EAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT

Jinke Wang, Xiangyang Zhang, Peiqing Lv +2

Purpose: This paper proposes a new network framework called EAR-U-Net, which leverages EfficientNetB4, attention gate, and residual learning techniques to achieve automatic and acc…