论文标题
用于稀疏视图锥束计算层析成像量重建的原始二重式UNET
Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction
论文作者
论文摘要
在本文中，用于稀疏视图CT重建的原始二重性UNET被修改为适用于锥形光束投影并执行整个体积而不是切片的重建。实验表明，与直接FDK重建相比，所提出的方法的PSNR增加了10dB，而仅使用23个投影时，与经过修改的原始原始二线网络相比，几乎3DB增加了。提出的网络未优化WRT。记忆消耗或超参数仅作为概念证明，仅限于低分辨率的预测和量。
In this paper, the Primal-Dual UNet for sparse view CT reconstruction is modified to be applicable to cone beam projections and perform reconstructions of entire volumes instead of slices. Experiments show that the PSNR of the proposed method is increased by 10dB compared to the direct FDK reconstruction and almost 3dB compared to the modified original Primal-Dual Network when using only 23 projections. The presented network is not optimized wrt. memory consumption or hyperparameters but merely serves as a proof of concept and is limited to low resolution projections and volumes.
