![]() #OSIRIX LITE REMOVE NOT FOR MEDICAL USAGE SOFTWARE#There are many commercial (fee-based) and open-source (free-of-charge) software packages for segmenting DICOM images to STL data, all of which can run on a general-purpose personal computer (PC). Of the approximately 100 file formats of 3D CAD data that are used as 3D native files and intermediate files, a stereolithography (STL) file format is the most commonly used format for 3D printing. For this purpose, DICOM images are now being segmented to a 3D computer-aided design (CAD) format for intermediate data, on which primary processing, such as region of interest (ROI) setting, can be performed. ģD printing of DICOM images works with stacked 2D images that must be segmented to a data format required by the 3D printer. Patient-specific 3D models are now being used in many situations within the oral and maxillofacial surgery fields, including education, surgical planning, and surgical simulation. Three-dimensional (3D) printing from DICOM images has become easier with the advancement of technologies such as medical engineering, imaging engineering, and the evolution and decreasing costs of hardware and software. When using these software packages, it is necessary to understand the characteristics of each.ĭigital Imaging and Communications in Medicine (DICOM) is the leading standard around the world within the medical imaging information field. In particular, the features of each software package appeared in the fine and thin areas of the osseous structures. Our results revealed that there are some differences between the software packages that perform the segmentation and STL creation of the DICOM image data. 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. 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. 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. 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. 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. The DICOM image file was then segmented and exported to an STL file using nine different commercial/open-source software packages. Multidetector row CT scanning was performed on a dry human mandible with two 10-mm-diameter bearing balls as a phantom. This study focuses and reports on the DICOM to STL segmentation performance for nine software packages. The quality of the 3D model is directly related to the quality of the STL data. After primary and secondary processing, including noise removal and hole correction, the STL data can be 3D printed. The DICOM images are not exported to STL data immediately, but segmentation masks are exported to STL models. 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. ![]()
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