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首页> 美国卫生研究院文献>Medical Physics >Demons deformable registration for CBCT-guided procedures in the head and neck: Convergence and accuracy
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Demons deformable registration for CBCT-guided procedures in the head and neck: Convergence and accuracy

机译：恶魔在头颈部进行CBCT指导的过程中的可变形配准：收敛性和准确性

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>Purpose: The accuracy and convergence behavior of a variant of the Demons deformable registration algorithm were investigated for use in cone-beam CT (CBCT)-guided procedures of the head and neck. Online use of deformable registration for guidance of therapeutic procedures such as image-guided surgery or radiation therapy places trade-offs on accuracy and computational expense. This work describes a convergence criterion for Demons registration developed to balance these demands; the accuracy of a multiscale Demons implementation using this convergence criterion is quantified in CBCT images of the head and neck.>Methods: Using an open-source “symmetric” Demons registration algorithm, a convergence criterion based on the change in the deformation field between iterations was developed to advance among multiple levels of a multiscale image pyramid in a manner that optimized accuracy and computation time. The convergence criterion was optimized in cadaver studies involving CBCT images acquired using a surgical C-arm prototype modified for 3D intraoperative imaging. CBCT-to-CBCT registration was performed and accuracy was quantified in terms of the normalized cross-correlation (NCC) and target registration error (TRE). The accuracy and robustness of the algorithm were then tested in clinical CBCT images of ten patients undergoing radiation therapy of the head and neck.>Results: The cadaver model allowed optimization of the convergence factor and initial measurements of registration accuracy: Demons registration exhibited TRE=(0.8±0.3) mm and NCC=0.99 in the cadaveric head compared to TRE=(2.6±1.0) mm and NCC=0.93 with rigid registration. Similarly for the patient data, Demons registration gave mean TRE=(1.6±0.9) mm compared to rigid registration TRE=(3.6±1.9) mm, suggesting registration accuracy at or near the voxel size of the patient images (1×1×2 mm3). The multiscale implementation based on optimal convergence criteria completed registration in 52 s for the cadaveric head and in an average time of 270 s for the larger FOV patient images.>Conclusions: Appropriate selection of convergence and multiscale parameters in Demons registration was shown to reduce computational expense without sacrificing registration performance. For intraoperative CBCT imaging with deformable registration, the ability to perform accurate registration within the stringent time requirements of the operating environment could offer a useful clinical tool allowing integration of preoperative information while accurately reflecting changes in the patient anatomy. Similarly for CBCT-guided radiation therapy, fast accurate deformable registration could further augment high-precision treatment strategies.
机译：>目的：研究了恶魔可变形配准算法的一种变体的准确性和收敛行为，该算法可用于头颈锥束CT（CBCT）引导的程序。在线使用可变形配准来指导诸如图像引导手术或放射疗法之类的治疗程序时，需要在准确性和计算费用上进行权衡。这项工作描述了为平衡这些需求而开发的恶魔注册的收敛标准。 >方法：使用开源“对称” Demons注册算法，基于变化的收敛标准，可以量化使用该收敛标准的多尺度Demons实现的准确性。在迭代之间的变形场中，通过优化精度和计算时间，可以在多级图像金字塔的多个级别中前进。在尸体研究中优化了收敛标准，该研究涉及使用为3D术中成像修改的外科C型臂原型获取的CBCT图像。进行了CBCT到CBCT的配准，并根据归一化互相关（NCC）和目标配准误差（TRE）量化了准确性。然后在10例接受头部和颈部放射治疗的患者的临床CBCT图像中测试了该算法的准确性和鲁棒性。>结果：尸体模型允许优化收敛因子并初步测量配准精度：恶魔配准在尸体头部显示TRE =（0.8±0.3）mm和NCC = 0.99，而刚性配准的TRE =（2.6±1.0）mm和NCC = 0.93。同样，对于患者数据，与刚性注册TRE =（3.6±1.9）mm相比，恶魔配准给出的平均TRE =（1.6±0.9）mm，这表明在患者图像的体素大小处（1×1×2）或附近的配准精度mm 3 ）。基于最佳收敛标准的多尺度实现在尸体头部完成52 s的注册，在较大的FOV患者图像中完成平均注册270 s。>结论：在恶魔中适当选择收敛和多尺度参数事实证明，在不牺牲注册性能的情况下，注册可以减少计算费用。对于具有可变形配准的术中CBCT成像，在严格的操作环境时间内执行精确配准的能力可以提供一种有用的临床工具，允许整合术前信息，同时准确反映患者解剖结构的变化。同样，对于CBCT引导的放射治疗，快速准确的可变形配准可以进一步增强高精度治疗策略。

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