Deng Jun-Min, Yue Hai-Zhen, Zhuo Zhi-Zheng, Yan Hua-Gang, Liu Di, Li Hai-Yun
School of biomedical engineering, Capital Medical University, Beijing, China, 100069,
J Med Syst. 2014 May;38(5):40. doi: 10.1007/s10916-014-0040-2. Epub 2014 Apr 13.
Image registration between planning CT images and cone beam-CT (CBCT) images is one of the key technologies of image guided radiotherapy (IGRT). Current image registration methods fall roughly into two categories: geometric features-based and image grayscale-based. Mutual information (MI) based registration, which belongs to the latter category, has been widely applied to multi-modal and mono-modal image registration. However, the standard mutual information method only focuses on the image intensity information and overlooks spatial information, leading to the instability of intensity interpolation. Due to its use of positional information, wavelet transform has been applied to image registration recently. In this study, we proposed an approach to setup CT and cone beam-CT (CBCT) image registration in radiotherapy based on the combination of mutual information (MI) and stationary wavelet transform (SWT). Firstly, SWT was applied to generate gradient images and low frequency components produced in various levels of image decomposition were eliminated. Then inverse SWT was performed on the remaining frequency components. Lastly, the rigid registration of gradient images and original images was implemented using a weighting function with the normalized mutual information (NMI) being the similarity measure, which compensates for the lack of spatial information in mutual information based image registration. Our experiment results showed that the proposed method was highly accurate and robust, and indicated a significant clinical potential in improving the accuracy of target localization in image guided radiotherapy (IGRT).
计划CT图像与锥形束CT(CBCT)图像之间的图像配准是图像引导放射治疗(IGRT)的关键技术之一。当前的图像配准方法大致可分为两类:基于几何特征的方法和基于图像灰度的方法。基于互信息(MI)的配准属于后一类,已广泛应用于多模态和单模态图像配准。然而,标准的互信息方法仅关注图像强度信息,而忽略了空间信息,导致强度插值的不稳定性。由于小波变换利用了位置信息,最近已被应用于图像配准。在本研究中,我们提出了一种基于互信息(MI)和静态小波变换(SWT)相结合的放射治疗中CT与锥形束CT(CBCT)图像配准方法。首先,应用SWT生成梯度图像,并消除在不同图像分解级别产生的低频分量。然后对剩余的频率分量进行逆SWT。最后,使用以归一化互信息(NMI)为相似性度量的加权函数对梯度图像和原始图像进行刚性配准,这弥补了基于互信息的图像配准中空间信息的不足。我们的实验结果表明,所提出的方法具有很高的准确性和鲁棒性,并在提高图像引导放射治疗(IGRT)中靶区定位的准确性方面显示出显著的临床潜力。