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An alternative approach to code, store, and regenerate 3D data in dental medicine using open-source software: A

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Journal of Dentistry
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PubMed
Summary

A new scripting technique using Python in Blender effectively manages 3D dental data. This method significantly reduces standard tessellation language (STL) file sizes and processing times without impacting accuracy, making dental data regeneration more efficient.

Keywords:
3d data managementBlender scriptingDentistryOpen-source software, accuracyStl file optimization

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Area of Science:

  • Digital Dentistry
  • Computational Geometry
  • Medical Data Management

Background:

  • Three-dimensional (3D) dental data, often in standard tessellation language (STL) format, presents challenges in file size and management.
  • Efficient handling of these digital models is crucial for various dental applications, including diagnostics and treatment planning.

Purpose of the Study:

  • To develop and evaluate a scripting-based technique for managing 3D dental data using Python and Blender.
  • To assess the impact of this technique on standard tessellation language (STL) file size, accuracy (trueness and precision), and processing time.

Main Methods:

  • Ten diverse STL dental models were processed using Python scripts generated by ChatGPT within Blender for mesh simplification and data compression.
  • Regenerated STL models were compared against original files for accuracy using GOM Inspect software.
  • Statistical analyses (Kruskal-Wallis, Mann-Whitney) were employed to evaluate differences in file sizes and processing times.

Main Results:

  • The scripting technique successfully generated, regenerated, and visualized STL models, achieving significantly reduced file sizes for both scripts and regenerated data (p < 0.001).
  • No significant loss in trueness was observed, with deviations as low as 0.0 µm to 6.8 µm.
  • All regenerated models exhibited perfect precision, and processing time showed a proportional relationship with original file sizes.

Conclusions:

  • A scripting-based approach using Python in Blender is effective for coding, storing, and regenerating 3D dental STL data.
  • This method significantly reduces file sizes and processing times without compromising data accuracy (trueness and precision).
  • The technique offers an efficient way to manage and reuse digital dental models.