配准算法对 PCA 单幅投影肺部重建的影响

肺癌放射治疗中,肺部肿瘤位置实成像对于临床意义重大。在一种利用单X射线投影进行成像的实时肺部3D成像算法中,图像配准过程引入的不准确对于PCA模型构建以及重建过程有重大影响。文章分析了光流法、Demons算法、水平集算法三种配准算法对重建效果的影响,并通过定性以及定量实验分析验证。结果表明,光流法配准在配准结果以及模型构建方面有较好的效果。

Deformable Image Registration Effect on PCA-based Reconstruction with Single X-ray Imaging

In modern lung cancer radiotherapy, it is important to have a precise knowledge of the real-time lung tumor position during the treatment delivery. For a real-time 3D lung imaging algorithm from a single X-ray projection image, the inaccuracies contributed by the image registration process affects much on the PCA modelling and construction process. We utilize 3 deformable image registration algorithms: Optical Flow method, Demons method and Levelset method to evaluate the effect. By making quantitative analysis and qualitative analysis, we get the conclusion: Optical Flow method works much better in registration and PCA modelling.