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SANet : Self-Attention U-Net for Binary Tooth Segmentation
Jin Kim(김진),Su Yang(양수),MinHyuk Choi(최민혁),Bosoung Jeoun(전보성),Wonjin Yi(이원진) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
Tooth region segmentation is essential in the dental field to make an appropriate surgical plan and aid clinical diagnosis. However, this process is very time-consuming, challenging and tedious. We propose a self-attention U-Net (SANet) for the fully automated tooth segmentation on panoramic dental X-ray images to address this problem. Experimental results show that the SANet achieves higher performance than the baseline segmentation method.