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Published on: February 23, 2024
Accuracy assessment of image-based surface meshing for volumetric computed tomography images in the craniofacial
Sang-Hoon Kang1, Moon-Key Kim, Hak-Jin Kim
1From the *Department of Oral and Maxillofacial Surgery, National Health Insurance Service, Ilsan Hospital, Goyang-si, Republic of Korea; †Department of Oral and Maxillofacial Surgery, College of Dentistry, Yonsei University, Seoul, Republic of Korea; ‡Department of Oral Maxillofacial Surgery, Stomatological Hospital of Guangzhou Medical College, Guangzhou, China.
Background:
Three-dimensional printing and computer-assisted surgery demand a high-precision three-dimensional mesh model created from computed tomography (CT) imaging data using an image-based meshing algorithm. We aimed to evaluate the three-dimensional geometric accuracy of surface meshes produced from CT images with commercially available software packages.
Methods:
The CT images were acquired for 3 human dry skulls and 10 manufactured plastic skulls. Four commercially available software packages were used to produce the surface meshes in stereolithography (STL) file format. These CT-based STL surface meshes were registered and compared with three-dimensional optical-scanned reference mesh surface for evaluating the accuracy of the STL mesh produced with each software package.
Results:
The surface geometries produced by the CT-image-based meshing process were all relatively accurate; differences from the three-dimensional optical-scanned data were in the voxel or subvoxel range. However, when comparisons with the three-dimensional optical-scanned surface data were performed in individual anatomic regions, we found significantly different accuracies of the CT-based STL surface meshes produced by the different software packages.
Conclusions:
We found that all 4 software packages showed reasonably good meshing accuracies for clinical use. However, the range of errors inherent in the CT-image-based meshing process demands that caution should be taken in selecting and manipulating the software to avoid potential errors in specific clinical applications.
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