论文标题
大脑18F-FDG PET图像在图像域中的深度学习衰减和散射校正
Deep Learning-Based Attenuation and Scatter Correction of Brain 18F-FDG PET Images in the Image Domain
论文作者
论文摘要
衰减和散射校正（AC）对于定量正电子发射断层扫描（PET）成像至关重要。最近，已经提出了使用深度学习方法在图像结构域中直接应用AC在缺乏伴随传播或解剖成像的混合宠物/MR和专用PET系统中。这项研究着手使用不同的输入设置研究图像域中的深度学习AC。
Attenuation and scatter correction (AC) is crucial for quantitative Positron Emission Tomography (PET) imaging. Recently, direct application of AC in the image domain using deep learning approaches has been proposed for the hybrid PET/MR and dedicated PET systems that lack accompanying transmission or anatomical imaging. This study set out to investigate deep learning-based AC in the image domain using different input settings.
