Imaging phantom

Nuclear medicine

Operating system

Computer graphics (images)

Artificial intelligence

Composite material

File size

Materials science

Programming language

Software

Computer science

DICOM

File format

Process (computing)

3d model

3D printing

Medicine

Database

Segmentation

3D Printing in Medicine

Background Extracting and three-dimensional (3D) printing an organ in a region of interest in DICOM images typically calls for segmentation as a first step in support of 3D printing. The DICOM images are not exported to STL data immediately, but 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 the DICOM to STL segmentation performance for nine software packages. Methods Multidetector row CT scanning was performed on a dry human mandible with two 10-mm-diameter bearing balls as a phantom. The DICOM image file was then segmented and exported to an 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 file 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 the observed differences between their shapes characterized as the 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, but no statistically significant differences 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 that in the other directions. The mean shape error between software packages of the mandibular STL model was 0.11 mm, but there was no statistically significant difference between them. Conclusions Our results revealed that there are some differences between the software packages that perform the segmentation and STL creation of the DICOM image data. In particular, the features of each software package appeared in the fine and thin areas of the osseous structures. When using these software packages, it is necessary to understand the characteristics of each.

DICOM segmentation and STL creation for 3D printing: a process and software package comparison for osseous anatomy