using osirix lite to segment for 3d print how

Using osirix lite to segment for 3d print how software#

Intraoral radiography and CBCT images revealed a C-shaped root canal in the mesial root, and compressive resorption of the distal root due to impingement of the crown of the horizontally impacted lower left third molar.

A 27-year-old woman visited this hospital for conservative treatment of the mandibular left second molar. Here, we describe a case of autotransplantation of a mandibular horizontally impacted third molar using a 3-dimensional (3D) model based on limited cone-beam computed tomography (CBCT) images for diagnosis, 3D morphological evaluation, preoperative treatment planning, and surgical simulation.

Using osirix lite to segment for 3d print how software#

When using these software packages, it is necessary to understand the characteristics of each. In particular, the features of each software package appeared in the fine and thin areas of the osseous structures. 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.Ĭonclusions: 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 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. Methods: 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.

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.