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NeurophotonicsNeurosciencePeer-reviewed journal article

Creating anatomically-derived, standardized, customizable, and three-dimensional printable head caps for functional neuroimaging

Ashlyn McCanniD, Edward XuiD, Fan-Yu YeniD, Noah Joseph, Qianqian FangiD

PDFDOIPreprint

Abstract

AbstractO_ST_ABSSignificanceC_ST_ABSConsistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of headgear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures. AimWe aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap. ApproachWe utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subjects anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain". ResultsUsing the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks. ConclusionsThe methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits person-alized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.

Citations
5
FWCI
1.22
Field percentile
top 26%

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