Spatial transformation and registration of brain images using elastically deformable models
Spatial transformation and registration of brain images using elastically deformable models
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DOI：
10.1006/cviu.1997.0605
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发表时间：
1997-05-01
影响因子：
4.5
通讯作者：
Davatzikos, C
中科院分区：
文献类型：
--
作者：
Davatzikos, C
断层脑图像的空间变换和配准算法的发展是几个临床和基础科学医学应用中的关键问题，包括计算机辅助神经外科，功能图像分析和形态测量学。本文介绍了一种基于弹性变形模型的脑图像空间变换技术。一个可变形的表面算法被用来找到一个参数表示的外皮层表面，然后定义在两个大脑图像中的相应的皮层区域之间的映射。基于所得到的映射，然后确定三维弹性扭曲变换，其使两个图像配准。该变换将图像建模为通过外部力场变形成彼此配准的不均匀弹性对象。图像的弹性属性可以从一个区域到另一个区域变化，允许更可变的大脑区域，例如脑室，比可变性较小的区域更自由地变形。最后，预应变弹性的框架被用来模拟结构的不规则性，特别是心室扩张发生的老化或疾病，以及肿瘤的生长。使用磁共振图像获得性能测量。(C)北京：科学出版社.
The development of algorithms for the spatial transformation and registration of tomographic brain images is a key issue in several clinical and basic science medical applications, including computer-aided neurosurgery, functional image analysis, and morphometrics. This paper describes a technique for the spatial transformation of brain images, which is based on elastically deformable models. A deformable surface algorithm is used to find a parametric representation of the outer cortical surface and then to define a map between corresponding cortical regions in two brain images. Based on the resulting map, a three-dimensional elastic warping transformation is then determined, which brings two images into register. This transformation models images as inhomogeneous elastic objects which are deformed into registration with each other by external force fields. The elastic properties of the images can vary from one region to the other, allowing more variable brain regions, such as the ventricles, to deform more freely than less variable ones. Finally, the framework of prestrained elasticity is used to model structural irregularities, and in particular the ventricular expansion occurring with aging or diseases, and the growth of tumors. Performance measurements are obtained using magnetic resonance images. (C) 1997 Academic Press.