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2023

EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation

Ruan, Jiacheng, Xie, Mingye, Gao, Jingsheng et al.

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Transformer and its variants have been widely used for medical image segmentation.

However, the large number of parameter and computational load of these models make them unsuitable for mobile health applications.
To address this issue, we propose a more efficient approach, the Efficient Group Enhanced UNet (EGE-UNet).
We incorporate a Group multi-axis Hadamard Product Attention module (GHPA) and a Group Aggregation Bridge module (GAB) in a lightweight manner.

EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation · Around

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