DICOM segmentation and STL creation for 3D Printing: A Process and Software Package Comparison for Osseous Anatomy

Abstract Background: Extracting and three-dimensional (3D) printing an organ in a region of interest in DICOM images typically calls for segmentation in support of 3D printing as a first step. The DICOM images are not exported to STL data immediately, segmentation masks are exported to STL models. After primary and secondary processing, including noise removal and hole correction, the STL data can be 3D printed. The quality of the 3D model is directly related to the quality of the STL data. This study focuses and reports on DICOM to STL segmentation performance for nine software packages.Methods: Multi-detector row CT scanning was performed on a dry human mandible with two 10-mm-diameter bearing balls as a phantom. The DICOM images file was then segmented and exported to a STL file using nine different commercial/open-source software packages. Once the STL models were created, the data (file) properties and the size and volume of each were measured and differences across the software packages were noted. Additionally, to evaluate differences between the shapes of the STL models by software package, each pair of STL models was superimposed, with observed differences between their shapes characterized as shape error. Results: The data (file) size of the STL file and the number of triangles that constitute each STL model were different across all software packages, there was no statistically significant difference were found across software packages. The created ball STL model expanded in the X-, Y-, and Z-axis directions, with the length in the Z-axis direction (body axis direction) being slightly longer than other directions. There were no significant differences in shape error across software packages for the mandible STL model. Conclusions: The different characteristics of each software package were noticeable, such as different effects in the thin cortical bone area, likely due to the partial volume effect, which may reflect differences in image binarization algorithms. Although the shape of the STL model differs slightly depending on the software, our results indicate that shape error in 3D printing for clinical use in the operation of osseous structures.