Suppr超能文献

通过轮廓拟合在无框架立体定向中实现功能与解剖结构的联合配准。

Co-registration of function and anatomy in frameless stereotaxy by contour fitting.

作者信息

Kober Helmut, Nimsky Christopher, Vieth Jürgen, Fahlbusch Rudolf, Ganslandt Oliver

机构信息

Department of Neurosurgery, University Erlangen-Nürnberg, Erlangen, Germany.

出版信息

Stereotact Funct Neurosurg. 2002;79(3-4):272-83. doi: 10.1159/000072396.

Abstract

We investigated a co-registration algorithm using a contour-fitting procedure to integrate functional data from magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) for frameless stereotaxy. In fMRI the shape of the head was reconstructed from anatomical images, in MEG it was scanned using an electromagnetic sensor position indicator. Functional information was transferred to the 3D-MR image set used for frameless stereotaxy by fitting the digitized (MEG) and reconstructed head shape (fMRI) to the 3D-MR images. The mean residual error of the contour fit was 2.3 mm for the MEG and 1.3 mm for the fMRI registration. According to computer simulations, the achievable transformation error is 0.75 and 0.5 mm, respectively. This method enables independent recording of functional and anatomical measurements with a co-registration accuracy better than 2 mm.

摘要

我们研究了一种使用轮廓拟合程序的配准算法,以整合来自脑磁图(MEG)和功能磁共振成像(fMRI)的功能数据用于无框架立体定向。在fMRI中,头部形状从解剖图像重建,在MEG中,使用电磁传感器位置指示器进行扫描。通过将数字化的(MEG)和重建的头部形状(fMRI)拟合到3D-MR图像,功能信息被转移到用于无框架立体定向的3D-MR图像集。MEG轮廓拟合的平均残余误差为2.3毫米,fMRI配准的平均残余误差为1.3毫米。根据计算机模拟,可实现的变换误差分别为0.75毫米和0.5毫米。该方法能够独立记录功能和解剖测量,配准精度优于2毫米。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验