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Updated: Jan 29, 2026

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使用深度学习对椎区域的年龄估计.

Zhiyong Zhang1,2, Ningtao Liu3, Ziyi Hu1,2

  • 1Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710004, China.

Bioengineering (Basel, Switzerland)
|January 28, 2026
PubMed
概括

深度学习模型使用椎区域 (SR) 和椎 (CV) 代表从横向头脑电图 (LCR) 显著提高年龄估计的准确性. 结合周围软组织的SR模式,在广泛的年龄范围 (4-40岁) 中表现出卓越的性能.

关键词:
年龄估计年龄估计.宫椎的区域是椎的区域.深度学习是一种深度学习.侧向头脑测量放射图片分段化面具的部分化面具.

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