摘要
目的胸主动脉腔内修复术(thoracic endovascular aortic repair,TEVAR)已经广泛应用于胸主动脉病变的治疗,成为传统主动脉开胸手术的可靠替代方案。然而,医生在术中看不到血管形态和位置,覆膜支架容易封堵主动脉重要分支而引发严重并发症。为了帮助医生导航支架,提出并实现了一种TEVAR术前CT血管造影(computed tomographic angiography,CTA)与术中X线图像的配准算法。方法首先,对影响CTA投影形状的参数高密度采样,利用采样获得的系列投影形变,分别对CTA全图和分割的CTA骨架进行数字影像重建(digitally reconstructed radiograph,DRR),将两者叠加起来,生成叠加DRR库;然后,以爬山优化,在叠加DRR库中寻找与X线图像归一化互信息最大的DRR图像,推算出投影形变,最终实现CTA与X线图像的配准。结果采用叠加DRR库的方法,配准了1例患者的术前CTA图像与一帧术中X线图像。与归一化互相关方法以及无骨架叠加的普通DRR库方法相比较,本方法获得了更为精确的配准结果。结论基于叠加DRR库的方法能有效配准术前CTA与术中X线图像。
Objective As a reliable alternative to traditional thoracic surgery,thoracic endovascular aortic repair（ TEVAR） has been widely used. During the operation,however,the vascular is invisible. Once the stent graft covers the important aortic branch arteries,serious complications will occur. Therefore,in order to guide the graft,we proposed a preoperative computed tomographic angiography（ CTA） and intraoperative X-ray image registration algorithm for TEVAR. Methods Firstly,using high-density sampling parameters,we generated two DRR sequences of CTA and of skeleton segmented from CTA. Overlapping the corresponding CTA DRR andskeleton DRR,we generated another DRR sequence called DRR library. Then,the parameter which maximized the generalized mutual information between X-ray image and DRR in the library was chosen with Hill Climbing as the registration result. Results Using overlapped DRR librarybased on this method,a CTA image and an X-ray image acquired from a patient in TEVAR were aligned.Compared with generalized cross-correlation based method and DRR library based on this method without skeleton,our approach got more accurate result. Conclusions Overlapped DRR library based on algorithm is valid for CTA and X-ray image registration in TEVAR.
出处
《北京生物医学工程》
2018年第1期91-95,共5页
Beijing Biomedical Engineering
