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Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques

Overview of attention for article published in Frontiers in Neuroscience, January 2017
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Title
Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques
Published in
Frontiers in Neuroscience, January 2017
DOI 10.3389/fnins.2017.00004
Pubmed ID
Authors

Xiang Xiao, Hao Zhu, Wei-Jie Liu, Xiao-Ting Yu, Lian Duan, Zheng Li, Chao-Zhe Zhu

Abstract

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS. As guidance for probe placement, the 10/20 system permits both proper ROI coverage and spatial consistency among multiple subjects and experiments in a MRI-free context. However, the traditional manual approach to the identification of 10/20 landmarks faces problems in reliability and time cost. In this study, we propose a semi-automatic method to address these problems. First, a novel head surface reconstruction algorithm reconstructs head geometry from a set of points uniformly and sparsely sampled on the subject's head. Second, virtual 10/20 landmarks are determined on the reconstructed head surface in computational space. Finally, a visually-guided real-time navigation system guides the experimenter to each of the identified 10/20 landmarks on the physical head of the subject. Compared with the traditional manual approach, our proposed method provides a significant improvement both in reliability and time cost and thus could contribute to improving both the effectiveness and efficiency of 10/20-guided MRI-free probe placement.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Student > Master 8 15%
Researcher 5 10%
Student > Bachelor 3 6%
Student > Doctoral Student 2 4%
Other 8 15%
Unknown 14 27%
Readers by discipline Count As %
Neuroscience 12 23%
Psychology 10 19%
Engineering 9 17%
Physics and Astronomy 1 2%
Business, Management and Accounting 1 2%
Other 2 4%
Unknown 17 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 January 2017.
All research outputs
#22,764,772
of 25,377,790 outputs
Outputs from Frontiers in Neuroscience
#10,138
of 11,542 outputs
Outputs of similar age
#363,829
of 422,653 outputs
Outputs of similar age from Frontiers in Neuroscience
#149
of 177 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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