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Updated: May 21, 2025

Author Spotlight: Streamlined Brain and Skull Modeling for Enhanced Neurosurgical Planning in NHP Research
Published on: February 9, 2024
Creating anatomically derived, standardized, customizable, and three-dimensional printable head caps for functional
Ashlyn McCann1, Edward Xu1, Fan-Yu Yen1
1Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States.
Significance:
Consistent and accurate probe placement is a crucial step toward enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. Although 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.
Aim:
We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, three-dimensional (3D) printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap.
Approach:
We utilize our advanced 3D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3D printable head cap model. The 3D 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."
Results:
Using 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 3D printable using off-the-shelf printers and filaments while accurately preserving the head geometry and landmarks.
Conclusions:
The 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 personalized 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.

