基于关键点的超声图像与磁共振图像多分辨率离散优化配准方法  

Multiresolution discrete optimization registration method of ultrasound and magnetic resonance images based on key points

作　　者：谭振霖 郭圣文 TAN Zhenlin;GUO Shengwen(School of Material Science and Engineering,South China University of Technology,Guangzhou 510640,P.R.China;School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,P.R.China)

机构地区：[1]华南理工大学材料学院,广州510640 [2]华南理工大学自动化学院,广州510640

出　　处：《生物医学工程学杂志》2023年第2期202-207,216,共7页Journal of Biomedical Engineering

基　　金：广州市科技计划项目(202102010421);广东省基础与应用基础研究基金项目(2021A1515220113)。

摘　　要：脑肿瘤手术规划及术中,术前磁共振(MR)图像与术中超声(US)图像的配准甚为关键。考虑到两种模态图像具有不同密度范围及分辨率,且超声图像存在较多的斑点噪声干扰,采用一种基于局部邻域信息的自相似性上下文(SSC)描述子定义图像之间的相似性测度。将超声图像作为参考,使用三维微分运算提取其中角点作为关键点,并采用密集位移采样离散优化算法实施配准。整个配准过程分为仿射配准和弹性配准两个阶段,在仿射配准阶段,对图像进行多分辨率分解,在弹性配准阶段,采取最小卷积和均值场推理策略对关键点的位移向量进行正则化处理。对22名患者的术前MR和术中US图像进行配准实验,仿射配准后的误差为(1.57±0.30)mm,每对图像配准平均耗时1.36 s;弹性配准后的误差为(1.40±0.28)mm,平均用时1.53 s。实验结果证明本文采用的方法具有良好的配准精度和速度。The registration of preoperative magnetic resonance(MR) images and intraoperative ultrasound(US) images is very important in the planning of brain tumor surgery and during surgery. Considering that the two-modality images have different intensity range and resolution, and the US images are degraded by lots of speckle noises, a selfsimilarity context(SSC) descriptor based on local neighborhood information was adopted to define the similarity measure.The ultrasound images were considered as the reference, the corners were extracted as the key points using threedimensional differential operators, and the dense displacement sampling discrete optimization algorithm was adopted for registration. The whole registration process was divided into two stages including the affine registration and the elastic registration. In the affine registration stage, the image was decomposed using multi-resolution scheme, and in the elastic registration stage, the displacement vectors of key points were regularized using the minimum convolution and mean field reasoning strategies. The registration experiment was performed on the preoperative MR images and intraoperative US images of 22 patients. The overall error after affine registration was(1.57 ± 0.30) mm, and the average computation time of each pair of images was only 1.36 s;while the overall error after elastic registration was further reduced to(1.40 ± 0.28) mm,and the average registration time was 1.53 s. The experimental results show that the proposed method has prominent registration accuracy and high computational efficiency.

关 键 词：超声图像 磁共振图像 配准 关键点 离散优化 多分辨率分解 

分 类 号：R445[医药卫生—影像医学与核医学] TP18[医药卫生—诊断学]