Study of DTI multi-channel registration based on the variable inertia coefficient active demons algorithm

doi:10.3969/j.issn.1000-1565.2021.04.014

Abstract

Abstract: The dassical Demons algorithm is an important image registration algorithm,which effect. The algorithm uses the gradient information of the reference image as the driving force to register the image. However, the registration effect is not good for large deformation and the convergence rate is slow. The algorithm of active demons uses the gradient information of the reference image and the floating image as the driving force to accelerate the convergence of the image. It is also applicable to registration of large deformation images and the topology is easy to change. In this work, demons algorithm was applied to DTI multi-channel image registration. The algorithm of this paper is improved based on variable parameter active demons. By introducing the coefficient of inertia b, DTI multi-channel- DOI:10.3969/j.issn.1000-1565.2021.04.014基于变惯性系数active demons算法的DTI多通道配准研究郑伟^1,2,3,周杨^1,2,3,李文华^1,2,3,刘帅奇^1,2,3,张晓丹⁴,马泽鹏⁴(1.河北大学电子信息工程学院,河北保定 071002;2.河北省数字医疗工程重点实验室,河北保定 071002;3.河北省机器视觉中心,河北保定 071002;4.河北大学附属医院 CT-MRI诊断科,河北保定 071000)摘要:经典的demons算法利用参考图像的梯度信息作为配准的驱动力来配准图像,但是只适用于小形变配准,对于大形变配准效果并不理想,且存在收敛速度慢的问题,active demons算法在demons算法基础上加入了浮动图像的灰度梯度信息,加快了图像的收敛速度,并且对于大形变图像配准同样适用,可是拓扑结构容易发生改变.本文在基于变参数active demons算法基础上做改进,通过引入惯性系数b,提出基于变惯性系数active demons算法的DTI多通道配准,将变参数active demons的改进算法应用于DTI多通道图像配准.经典的active demons算法、变参数active demons算法和本文算法的MSE图做比较,可以发现本文算法可以进一步提高配准的收敛速度和精度,也使图像的拓扑结构得到很好的保持.关键词:梯度信息;大形变;驱动力;拓扑结构;非刚性配准中图分类号:TN911 文献标志码:A 文章编号:1000-1565(2021)04-0436-07Study of DTI multi-channel registration based on the variable inertia coefficient active demons algorithmZHENG Wei^1,2,3,ZHOU Yang^1,2,3,LI Wenhua^1,2,3,LIU Shuaiqi^1,2,3,ZHANG Xiaodan⁴,MA Zepeng⁴(1. College of Electronic and Information Engineering, Hebei University, Baoding 071002, China; 2. Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding 071002, China;3. Machine Vision Engineering Research Center of Hebei Province, Baoding 071002, China;4. Department of CT-MRI, Affiliated Hospital of Hebei University, Baoding 071000, China)Abstract: The dassical Demons algorithm is an important image registration algorithm,which effect. The algorithm uses the gradient information of the reference image as the driving force to register the image. However, the registration effect is not good for large deformation and the convergence rate is slow. The algorithm of active demons uses the gradient information of the reference image and the floating image as the driving force to accelerate the convergence of the image. It is also applicable to registration of large deformation images and the topology is easy to change. In this work, demons algorithm was applied to DTI multi-channel image registration. The algorithm of this paper is improved based on variable parameter active demons. By introducing the coefficient of inertia b, DTI multi-channel- 收稿日期:2020-03-14 基金项目:国家自然科学基金资助项目(2014000000;61401308;61572063);河北省自然科学基金资助项目(F2020201025; H2020201021) 第一作者:郑伟(1972—),女,黑龙江兰西人,河北大学教授,博士,主要从事图像处理与分析、图像安全通信、图像加密和隐藏研究. E-mail:147685650@qq.com 通信作者:马泽鹏(1989—),男,河北保定人,河北大学附属医院医师,主要从事脑部和心脏疾病的CT、MR、fMRI的诊断及鉴别诊断.E-mail:mzpdan@163.com第4期郑伟等:基于变惯性系数active demons算法的DTI多通道配准研究registration based on variable inertia factor Active demons algorithm was proposed. Comparison was made between the MSE graphs of the three algorithms, namely, the classical Active demons algorithm, the variable parameter Active demons algorithm and the algorithm. It can be found that the algorithm in this paper can further improve the convergence speed and accuracy of registration. Meanwhile, the topological structure of the image remains unchanged.

Key words: gradient information, large deformation, driving force, topology, nonrigid registration

CLC Number:

TN911

ZHENG Wei,ZHOU Yang,LI Wenhua,LIU Shuaiqi,ZHANG Xiaodan,MA Zepeng. Study of DTI multi-channel registration based on the variable inertia coefficient active demons algorithm[J]. Journal of Hebei University(Natural Science Edition), 2021, 41(4): 436-442.

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