Scientists have presented an open-source Python software called Normscan that generates 3D models from CT images for 3D printing and clinical use. The software, developed by George R. Nahass and colleagues, is intended to support surgical planning and execution for cranial malformations such as craniosynostosis.
Normscan uses a database of pediatric CT scans to generate normative models. Users upload their scans, define landmarks such as basion, nasion and the porions and the software registers and averages the models using an iterative closest point algorithm. The result is highly precise, printable 3D models.
The software is characterized by a simple user interface and high reproducibility. The variation coefficients for surface area and volume of the average model are less than 3 percent in ten test runs. The generated models can be 3D printed or visualized using augmented reality.
Normscan offers a comprehensive pipeline for creating averaged skull models and is suitable for building demographic-specific anatomical databases as well as for supporting surgical interventions. Originally developed for the correction of craniosynostosis, the modular software can be transferred to many areas of surgical planning and research thanks to its expandability.
More information can be found in the scientific paper “Normscan: open-source Python software to create average models from CT scans“
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