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Updated: May 6, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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基于高光谱技术的良性-恶性甲状腺结节的分类

Junjie Wang1,2,3, Jian Du1,3, Chenglong Tao1,3

  • 1Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.

Sensors (Basel, Switzerland)
|May 25, 2024
PubMed
概括

这项研究引入了一种快速的超光谱成像方法,用于在手术期间诊断甲状腺结节. 在区分良性与恶性甲状腺瘤方面,V3Dnet算法达到84.63%的准确性.

关键词:
这是分类分类的分类.超光谱图像的使用频谱特征 频谱特征 频谱特征甲状腺结节 甲状腺结节

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