分割
结核(地质)
人工智能
接头(建筑物)
计算机科学
鉴别诊断
甲状腺
图像分割
计算机视觉
放射科
模式识别(心理学)
超声波
生物医学工程
医学
病理
工程类
生物
内科学
古生物学
建筑工程
作者
Fang Chen,Haojie Han,Peng Wan,Hongen Liao,Chunrui Liu,Daoqiang Zhang
标识
DOI:10.1109/tbme.2023.3262842
摘要
Empirical results of clinical data showed that our Trans-CEUS model achieved not only a good lesion segmentation result with a high Dice similarity coefficient of 82.41%, but also superior diagnostic accuracy of 86.59%. Conclusion & significance: This research is novel since it is the first to incorporate the transformer into CEUS analysis, and it shows promising results on dynamic CEUS datasets for both segmentation and diagnosis tasks of the thyroid nodule.
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