Abstract
AbstractImage templates are a common tool for neuroscience research. Often, they are used for spatial normalization of magnetic resonance imaging (MRI) data, which is a necessary procedure for analyzing brain morphology and function via voxel-based analysis. This allows the researcher to reduce individual shape differences across images and make inferences across multiple subjects. Many templates have a small field-of-view typically focussed on the brain, limiting the use for applications requiring detailed information about other extra-cranial structures in the head and neck area. However, there are several applications where such information is important, for example source reconstruction of electroencephalography (EEG) and/or magnetoencephalography (MEG). We have constructed a new template based on 225 T1w and FLAIR images with a big field-of-view that can serve both as target for across subject spatial normalization as well as a basis to build high-resolution head models. This template is based on and iteratively re-registered to the MNI152 space to provide maximal compatibility with the most commonly used brain MRI template.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献