术前计划系统中CT造影图像的配准

Registration of Computer Temographic Images in Preoperation Planning

肾脏术前计划系统首先需要实现肾脏CT造影信息的融合,实现该信息融合需要进行以肾脏为中心的腹部三维CT造影图像的配准.本文首先采用基于DDCM可形变模型的半自动分割方法从CT扫描图像中分割出肾脏轮廓线,然后对轮廓线进行重建得到肾脏的二值体数据,该二值体数据膨胀后与原CT扫描图像重建出的灰度体数据求交,即得到完全包含肾脏的灰度体数据,最后采用互信息最大化的方法对重建得到的肾脏体数据进行配准.本文分析了配准过程中初始化参数对局部极值产生的影响,并应用几何矩的性质进行参数初始化,避免陷入局部极值.实验结果表明,本文方法能够实现以肾脏为中心的术前CT造影图像的配准,并且配准的精度和速度能够满足实际应用的需要.

Fusion of CT urography images is necessary in kidney preoperative planning system. A kidney-centered registration is the first step in the fusion. In this paper, several steps were taken to achieve this goal. Semi-automatic segmentation based on DDCM model was first performed to segment the kidney contours from CT slices. A binary kidney volume was obtained by contours reconstruction. The binary volume was then intersected with the original gray volume after 3D dilatation. Finally, rigid registration between the kidney gray volumes was accomplished. The effect of initial parameters during registration was analyzed. Characteristics of geometric moments were applied to initialize parameters in order to avoid local extrema. Experimental results show that the proposed method can realize a kidney-centered registration between CT acquisitions, and the precision and speed can meet practical requirements.