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Updated: May 12, 2026

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基于学习的多材料CBCT图像重建,使用超慢kV切换.

Chenchen Ma1, Jiongtao Zhu2, Xin Zhang3

  • 1School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China.

Journal of X-ray science and technology
|May 12, 2025
PubMed
概括

本研究介绍了SkV-Net,这是一种深度学习方法,用于光谱圆束CT (CBCT) 成像中的多材料分解. 这种新的方法使用超慢kV切换精确区分和骨等材料.

关键词:
缓慢的 kV 切换深度神经网络是一个神经网络.多种材料的分解分解.频谱成像技术的使用.

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