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Updated: Jun 18, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

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DSTAN:一个可变形的时空注意力网络,具有双向序列特征精细化,用于消除甲状腺超声波视频中的斑点噪声

Jianning Chi1,2, Jian Miao3, Jia-Hui Chen4

  • 1Faculty of Robot Science and Engineering, Northeastern University, Zhihui Street, Shenyang, 110169, Liaoning, China. chijianning@neu.edu.cn.

Journal of imaging informatics in medicine
|June 5, 2024
PubMed
概括

这项研究引入了一种新型可变形的时空注意力网络,以有效地消除甲状腺超声波视频,通过保存关键的纹理细节和减少文物来提高诊断准确性,以获得更清晰的医学成像.

关键词:
深度学习是一种深度学习.可变形的注意力注意力剩余卷积的卷积时间空间的注意力.甲状腺超声波视频视频视频拒绝声控的视频

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Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis05:41

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