非介入式手术导航中医学图像配准算法

提出一种用于非介入手术导航中基于自由变形模型的多模态医学图像非刚性配准方法,对术前MRI/CT和术中超声图像中都可见的血管结构进行配准.当图像对准时,一种图像中的血管中心点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、局部形变采用基于函数控制B样条的自由变形模型来描述;采用遗传算法和共轭梯度法相结合达到最小化目标函数.将文中算法应用于体模和临床数据,在配准精度和收敛速度上都取得了良好的效果.

Medical Image Registration Algorithm in Image-Guided Noninvasive Surgery

This paper describes a nonrigid registration method of multimodal medical images based on free form deformation, applied in image-guided noninvasive surgery. By the method, it registers pre-operative MRI or CT images with intra-operative ultrasound images based on the vessels visible in both of the modalities. When the images are aligned, the centerline points of the vessels in one image will align with the intensity ridge points in the other image. Rigid transformation is adopted in global registration while local deformation is described by a free form deformation based on a function controlled B-spline. The method applies an optimization strategy combining the genetic algorithm with the conjugated gradient algorithm to minimize the objective function. Two experiments were designed on phantom data and clinical data to evaluate the method, and the results indicate that the average standard deviation of the final transformation parameters is sub-voxel, sub-millimeter, and within 0.010 radians. The results show that the method has good registration accuracy and convergence rate. And it can be applied efficiently in the image-guided noninvasive surgery system.