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三维线性和非线性变换:光学显微镜与磁共振成像数据的整合

Three-dimensional linear and nonlinear transformations: an integration of light microscopical and MRI data.

作者信息

Schormann T, Zilles K

机构信息

C. and O. Vogt Institute of Brain Research, Heinrich-Heine University Düsseldorf, Germany.

出版信息

Hum Brain Mapp. 1998;6(5-6):339-47. doi: 10.1002/(SICI)1097-0193(1998)6:5/6<339::AID-HBM3>3.0.CO;2-Q.

Abstract

The registration of image volumes derived from different imaging modalities such as MRI, PET, SPECT, and CT has been described in numerous studies in which functional and morphological data are combined on the basis of macrostructural information. However, the exact topography of architectural details is defined by microstructural information derived from histological sections. Therefore, a technique is developed for integrating micro- and macrostructural information based on 1) a three-dimensional reconstruction of the histological volume which accounts for linear and nonlinear histological deformations, and 2) a two-step procedure which transforms these volumes to a reference coordinate system. The two-step procedure uses an extended principal axes transformation (PAT) generalized to affine transformations and a fast, automated full-multigrid method (FMG) for determining high-dimensional three-dimensional nonlinear deformations in order to account for differences in the morphology of individuals. With this technique, it is possible to define upwards of 1,000 times the resolution of approximately 1 mm in MRI, making possible the identification of geometric and texture features of microscopically defined brain structures.

摘要

来自不同成像模态(如MRI、PET、SPECT和CT)的图像体积配准在众多研究中已有描述,这些研究基于宏观结构信息将功能和形态学数据相结合。然而,结构细节的确切拓扑结构由源自组织学切片的微观结构信息定义。因此,开发了一种基于以下两点整合微观和宏观结构信息的技术:1)对组织学体积进行三维重建,该重建考虑了线性和非线性组织学变形;2)一种两步程序,将这些体积转换到参考坐标系。两步程序使用推广到仿射变换的扩展主轴变换(PAT)和一种快速、自动的全多重网格方法(FMG)来确定高维三维非线性变形,以考虑个体形态的差异。使用这种技术,可以定义比MRI中约1毫米分辨率高出1000倍以上的分辨率,从而能够识别微观定义的脑结构的几何和纹理特征。

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