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Updated: Mar 12, 2026

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背景感知变压器GAN用于直接生成减弱和散射纠正的PET数据

Mojtaba Jafaritadi1, Emily Anaya2, Garry Chinn1

  • 1Department of Radiology, Stanford University, Stanford, CA 94305 USA.

IEEE transactions on radiation and plasma medical sciences
|March 11, 2026
PubMed
概括

本研究引入了一个深度学习框架,使用条件生成对抗网络 (cGAN) 来从未经过校正的图像中创建校正的正电子发射断层扫描 (PET) 图像. 斯温-GAN模型表现出高精度,可以在没有传输扫描的情况下实现更好的图像质量.

关键词:
减弱校正的纠正 减弱校正的纠正有关PET/MRI的研究.深度学习 (DL) 是指深度学习.生成性的对抗性网络.定子发射断层扫描 (PET) 是一种分散的纠正纠正分散的纠正.转移窗口变压器的变压器视觉变压器 视觉变压器

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