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在HR-pQCT骨图像中使用深度学习模拟sinogram域运动和纠正图像域人工物.

Farhan Sadik1, Christopher L Newman2, Stuart J Warden3

  • 1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.

IEEE transactions on radiation and plasma medical sciences
|November 3, 2025
PubMed
概括

研究人员开发了一种深度学习方法来纠正高分辨率外围定量计算断层扫描 (HR-pQCT) 骨图像中的运动文物. 这种边缘增强的自我注意力Wasserstein带梯度惩罚的生成对抗网络 (ESWGAN-GP) 改善了骨微观结构的评估.

关键词:
骨头 骨头 骨头 骨头深度学习 (Deep Learning) 是一种深度学习.在ESWGAN-GP的比赛中.人力资源-pQCTCT 在运动 运动运动.这是一个SNR,SNR是SNR.在SSIM中,SSIM是SSIM.阴影图 (Sinogram) 是一个阴影图.这是VIF的VIF.

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