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A Semi-automatic Cranial Implant Design Tool Based on Rigid ICP Template Alignment and Voxel Space Reconstruction

Michael Lackner, Behrus Puladi, Jens Kleesiek, Jan Egger, Jianning Li

TL;DR

The paper tackles the challenge of designing patient-specific cranial implants (PSIs) for cranioplasty by introducing a semi-automatic design tool with a GUI that guides users through area-of-interest selection, rigid ICP-based template alignment, and voxel-space reconstruction. The method emphasizes clipping near the defect border to improve alignment and uses a voxel-grid fusion workflow with thresholding and post-processing to produce a final implant mesh, with the tool being open-source. Experimental evaluation on the AutoImplant dataset demonstrates that clipping improves alignment and reduces false positives, though limitations of rigid ICP (such as non-tangential border transitions and occasional brain penetration) remain. Overall, the work presents a practical, open-source path toward semi-automated PSI creation and highlights directions for enhanced automation and advanced post-processing to further reduce manual intervention and improve fit.

Abstract

In traumatic medical emergencies, the patients heavily depend on cranioplasty - the craft of neurocranial repair using cranial implants. Despite the improvements made in recent years, the design of a patient-specific implant (PSI) is among the most complex, expensive, and least automated tasks in cranioplasty. Further research in this area is needed. Therefore, we created a prototype application with a graphical user interface (UI) specifically tailored for semi-automatic implant generation, where the users only need to perform high-level actions. A general outline of the proposed implant generation process involves setting an area of interest, aligning the templates, and then creating the implant in voxel space. Furthermore, we show that the alignment can be improved significantly, by only considering clipped geometry in the vicinity of the defect border. The software prototype will be open-sourced at https://github.com/3Descape/Cranial_Implant_Design

A Semi-automatic Cranial Implant Design Tool Based on Rigid ICP Template Alignment and Voxel Space Reconstruction

TL;DR

The paper tackles the challenge of designing patient-specific cranial implants (PSIs) for cranioplasty by introducing a semi-automatic design tool with a GUI that guides users through area-of-interest selection, rigid ICP-based template alignment, and voxel-space reconstruction. The method emphasizes clipping near the defect border to improve alignment and uses a voxel-grid fusion workflow with thresholding and post-processing to produce a final implant mesh, with the tool being open-source. Experimental evaluation on the AutoImplant dataset demonstrates that clipping improves alignment and reduces false positives, though limitations of rigid ICP (such as non-tangential border transitions and occasional brain penetration) remain. Overall, the work presents a practical, open-source path toward semi-automated PSI creation and highlights directions for enhanced automation and advanced post-processing to further reduce manual intervention and improve fit.

Abstract

In traumatic medical emergencies, the patients heavily depend on cranioplasty - the craft of neurocranial repair using cranial implants. Despite the improvements made in recent years, the design of a patient-specific implant (PSI) is among the most complex, expensive, and least automated tasks in cranioplasty. Further research in this area is needed. Therefore, we created a prototype application with a graphical user interface (UI) specifically tailored for semi-automatic implant generation, where the users only need to perform high-level actions. A general outline of the proposed implant generation process involves setting an area of interest, aligning the templates, and then creating the implant in voxel space. Furthermore, we show that the alignment can be improved significantly, by only considering clipped geometry in the vicinity of the defect border. The software prototype will be open-sourced at https://github.com/3Descape/Cranial_Implant_Design
Paper Structure (11 sections, 6 figures, 1 table)

This paper contains 11 sections, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Methods
  3. Iterative Closest Point
  4. Application Prototype
  5. Experiments and Results
  6. Data
  7. Experiment
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgments

Figures (6)

  • Figure 1: An overview of the user interface and the available settings of the software prototype. Most of the settings are optional.
  • Figure 2: In the top right image we see that a lot of the artefacts are still connected with the implant after subtraction. When applying an offsetting to the target before the subtraction (bottom left) the artefacts are disconnected and can therefore easily be removed with the grid operators (bottom right).
  • Figure 3: Comparison of reconstructions options with (b) and without (a) clipping.
  • Figure 4: A reconstruction of the bilateral region viewed from outside (a) and inside (b) of the skull.
  • Figure 5: Signed distance colormap (a,b) between the reconstructed implant and the ground truth. Green indicates a distance of 0.
  • ...and 1 more figures