摘要
目前,医疗图像设备层出不穷,各种图像格式相继诞生。医疗图像所包涵的信息丰富程度和准确度直接影响到医生诊断治疗的结果。此篇文章以提供信息更为丰富、更为准确的多模图像,以便于医生临床的诊断治疗为目的,应用了刚性校正与双线性插值算法,以及聚类算法实现单模态PET与PET图像之间的配准,CT与CT图像之间的配准,与PET-CT图像的双模配准,这些方法在实际临床医学应用中有着重要的用途,对医生判断病灶的情况和确切位置有很大的帮助。
Nowadays there are different kinds of medical imaging equipments accompanied with different kinds of medical images. The information an image contains and its accuracy have an direct impact on the medical diagnosis and therapy results. This paper aims at providing doctors with images which have more information and make the diagnosis and therapy convenient. It uses the methods of stiff adjustment, bilinear interpose and the clustering arithmetic. As a result, the registrations of PET and PET, CT and CT,then PET and CT are realized. These methods have deep influence on the application of practical clinic medical skill and it helps the doctors to address the focus easily.
出处
《计算机仿真》
CSCD
2007年第8期191-193,197,共4页
Computer Simulation
关键词
正电子断层扫描
配准
单模态
多模态
聚类
PET
Image registration
Single modality
Multimodality
Clustering
