激光与光电子学进展, 2020, 57 (10): 101007, 网络出版: 2020-05-08   

基于B样条和水平集方法的医学图像联合分割与配准 下载: 796次

Joint Segmentation and Registration of Medical Image Based on B-Spline and Level Set Method
作者单位
江西理工大学信息工程学院, 江西 赣州 341000
摘要
针对分层B样条非刚性配准存在局部极值以及水平集分割方法不适用于噪声图像分割的问题,提出了一种基于局部更新分层B样条双向变换和水平集方法的医学图像联合分割与配准方法。该方法在分割算法中加入配准变换,在配准中融入图像分割的结构信息。使用B样条水平集函数对变换和分割的图像进行平滑表示,并在配准中引入双向变换以提高配准的精度和平滑性。在水平集方法的基础上,引入双向分层B样条变换构造分割与配准的联合能量泛函,并结合梯度下降法将能量泛函最小化以优化目标函数。实验结果表明:本方法与单独的图像分割方法相比,Dice度量均在99%以上;与单独的图像配准方法相比,均方误差下降了30%,能够提高图像的配准精度,且在分割噪声图像时有较好的鲁棒性。
Abstract
Aim

ing at the problems that non-rigid registration of layered B-spline exists local extremum and the level set segmentation method is not suitable for noisy image segmentation, a joint segmentation and registration of medical image based on locally updated hierarchical B-spline bidirectional transformation and level set method is proposed. The proposed method adds a registration transformation to the segmentation algorithm, and the structure information of image segmentation is incorporated into the registration. The B-spline level set function is used to smooth the transformed and segmented image, and a two-way transformation is introduced in the registration to improve the accuracy and smoothness of the registration. Based on the level set method, the bi-directional layered B-spline transform is introduced to construct the joint energy functional of segmentation and registration, and the gradient descent method is used to minimize the energy functional to optimize the objective function. Experimental results show that the Dice metric is always above 99% and the mean square error is reduced by 30% compared with the single image segmentation method. The proposed method improves the registration accuracy and has better robustness in noise image segmentation.

吕凯, 吴军. 基于B样条和水平集方法的医学图像联合分割与配准[J]. 激光与光电子学进展, 2020, 57(10): 101007. Kai Lü, Jun Wu. Joint Segmentation and Registration of Medical Image Based on B-Spline and Level Set Method[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101007.

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