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Cranial Implant Design Applying Shape-Based Interpolation Method via Open-Source Software

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Reconstructing a large skull defect is a challenge, as it normally involves the use of sophisticated proprietary image processing and expensive CAD software. As an alternative, open-source software can be used for this purpose. This study aimed to compare the 3D cranial implants reconstructed from computed tomography (CT) images using the open-source MITK software with commercial 3-matic software for ten decompressive craniectomy patients. The shape-based interpolation method was used, in which the technique of segmenting every fifth and tenth slice of CT data was performed. The final design of patient-specific implants from both software was exported to STL format for analysis. The results of the Kruskal–Wallis test for the surface and volume of cranial implants designed using 3-matic and the two MITK techniques showed no significant difference, p > 0.05. The results of the Hausdorff Distance (HD) and Dice Similarity Coefficient (DSC) analyses for cranial implants designed using 3-matic software and the two different MITK techniques showed that the average points distance for 3-matic versus MITK was 0.28 mm (every tenth slice) and 0.15 mm (every fifth slice), and the similarity between 3-matic and MITK on every tenth and fifth slices were 85.1% and 89.7%, respectively. The results also showed that the open-source MITK software is comparable with the commercial software for designing patient-specific implants.
Title: Cranial Implant Design Applying Shape-Based Interpolation Method via Open-Source Software
Description:
Reconstructing a large skull defect is a challenge, as it normally involves the use of sophisticated proprietary image processing and expensive CAD software.
As an alternative, open-source software can be used for this purpose.
This study aimed to compare the 3D cranial implants reconstructed from computed tomography (CT) images using the open-source MITK software with commercial 3-matic software for ten decompressive craniectomy patients.
The shape-based interpolation method was used, in which the technique of segmenting every fifth and tenth slice of CT data was performed.
The final design of patient-specific implants from both software was exported to STL format for analysis.
The results of the Kruskal–Wallis test for the surface and volume of cranial implants designed using 3-matic and the two MITK techniques showed no significant difference, p > 0.
05.
The results of the Hausdorff Distance (HD) and Dice Similarity Coefficient (DSC) analyses for cranial implants designed using 3-matic software and the two different MITK techniques showed that the average points distance for 3-matic versus MITK was 0.
28 mm (every tenth slice) and 0.
15 mm (every fifth slice), and the similarity between 3-matic and MITK on every tenth and fifth slices were 85.
1% and 89.
7%, respectively.
The results also showed that the open-source MITK software is comparable with the commercial software for designing patient-specific implants.

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