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基于变压器和U-Net的超声波图像细分,具有联合损失

Lina Cai1, Qingkai Li2, Junhua Zhang3

  • 1Yunnan Vocational Institute of Energy Technology, Qujing, Yunnan, China.

PeerJ. Computer science
|December 11, 2023
PubMed
概括

本研究介绍了TU-Net,这是一个混合深度学习模型,将Transformer和U-Net架构结合起来,以改进超声波图像细分. 图联网提高了医疗图像细分的准确性和概括性,优于现有的方法.

关键词:
注意力机制注意力机制共同的损失共同的损失变压器 变压器 变压器这就是U-Net.超声波图像细分 超声波图像细分

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