Song Guoli, Han Jianda, Zhao Yiwen, Wang Zheng, Du Huibin
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang110016, China.
University of Chinese Academy of Sciences, Beijing100049, China.
Curr Med Imaging Rev. 2017 Aug;13(3):274-283. doi: 10.2174/1573405612666160920123955.
In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem.
The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images.
The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process.
The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration.
在临床治疗过程中,医生需要多种医学媒介来提供有关患者的准确和完整信息。医学图像配准技术可以为医生提供更丰富的诊断和治疗信息,并为将图像配准作为一个优化问题进行研究的人员提供全面的参考来源。
图像配准的本质是将两个或多个不同图像进行空间关联,并获取它们空间关系的转换。对于医学图像配准,其过程并非绝对。其核心目的是找到不同图像之间的转换关系。
图像配准的主要步骤包括几何尺寸的变化、图像组合的变化、图像相似性度量、迭代优化和插值过程。
本综述的贡献在于梳理了相关图像配准研究方法,可为图像配准研究人员提供简要参考。