一种基于模式控制自由变形的非刚性医学图像配准算法

目的 对手术前MRI／CT图像和手术中超声图像两种模态下都可见的血管结构进行配准。方法 提出一种基于自由变形模型的多模态医学图像的非刚性配准的方法。当两个图像对准时，一种图像中的血管中心点就会对应着另一种图像下灰度脊点。对于全局变换采用刚性变换，而对于局部的形变，采用一种基于模式控制B样条的自由变形模型（FFD）来描述。配准算法采用遗传算法和共轭梯度法结合的优化策略来最小化目标函数。结果 我们设计了两个实验，分别应用于体模和临床数据来评价我们的算法。这种方法是连续而且准确的。最后的变换参数的均方差值是亚像素、亚毫米级的，在0．010弧度以内的。结论 实验结果显示本方法从配准精度和收敛速度上都得到了良好的效果。可以有效地应用于超声图像导航手术系统。

A Non-rigid Medical Image Registration Algorithm Based on Modally Controlled Free Form Deformation

Objective To register pre-operative MRI/CT images with intra-operative ultrasound images based on vessels visible in both of the modalities. Method A non-rigid registration method of multimodal medical images based on Free Form Deformation(FFD) was proposed. When the images were aligned, the centerline points of the vessels in one image aligned with the intensity ridge points in the other image. Rigid transformation was adopted in global registration while local deformation was described by a Free Form Deformation based on a modally controlled B-spline. The method applied an optimization strategy combining the genetic algorithm with the conjugated gradients algorithm to minimize the objective function. Result Two experiments were designed on phantom and clinical data to evaluate the method. The results demonstrated that the registration method was consistent accurate. The average standard deviation of the final transformation parameters was sub-voxel, sub-millimeter, and within 0.010 radians. Conclusion The results show that the method has good registration accuracy and convergence rate. It can be applied efficiently in the ultrasound-image-guided surgery system.