摘要
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。
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.
出处
《集成技术》
2015年第3期62-68,共7页
Journal of Integration Technology
基金
广东省引进科研创新团队项目(2011S013)
关键词
实时肺部3D成像
主成分分析
弹性配准
real-time 3D tumor localization
principal component analysis
deformable image registration
