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CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation

In-house fabrication of three-dimensional (3D) models for medical use has become easier in recent years. Cone beam computed tomography (CBCT) images are increasingly used as source data for fabricating osseous 3D models. The creation of a 3D CAD model begins with the segmentation of hard and soft ti...

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Autores principales: Kamio, Takashi, Kawai, Taisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000442/
https://www.ncbi.nlm.nih.gov/pubmed/36900065
http://dx.doi.org/10.3390/diagnostics13050921
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author Kamio, Takashi
Kawai, Taisuke
author_facet Kamio, Takashi
Kawai, Taisuke
author_sort Kamio, Takashi
collection PubMed
description In-house fabrication of three-dimensional (3D) models for medical use has become easier in recent years. Cone beam computed tomography (CBCT) images are increasingly used as source data for fabricating osseous 3D models. The creation of a 3D CAD model begins with the segmentation of hard and soft tissues of the DICOM images and the creation of an STL model; however, it can be difficult to determine the binarization threshold in CBCT images. In this study, how the different CBCT scanning and imaging conditions of two different CBCT scanners affect the determination of the binarization threshold was evaluated. The key to efficient STL creation through voxel intensity distribution analysis was then explored. It was found that determination of the binarization threshold is easy for image datasets with a large number of voxels, sharp peak shapes, and narrow intensity distributions. Although the intensity distribution of voxels varied greatly among the image datasets, it was difficult to find correlations between different X-ray tube currents or image reconstruction filters that explained the differences. The objective observation of voxel intensity distribution may contribute to the determination of the binarization threshold for 3D model creation.
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spelling pubmed-100004422023-03-11 CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation Kamio, Takashi Kawai, Taisuke Diagnostics (Basel) Article In-house fabrication of three-dimensional (3D) models for medical use has become easier in recent years. Cone beam computed tomography (CBCT) images are increasingly used as source data for fabricating osseous 3D models. The creation of a 3D CAD model begins with the segmentation of hard and soft tissues of the DICOM images and the creation of an STL model; however, it can be difficult to determine the binarization threshold in CBCT images. In this study, how the different CBCT scanning and imaging conditions of two different CBCT scanners affect the determination of the binarization threshold was evaluated. The key to efficient STL creation through voxel intensity distribution analysis was then explored. It was found that determination of the binarization threshold is easy for image datasets with a large number of voxels, sharp peak shapes, and narrow intensity distributions. Although the intensity distribution of voxels varied greatly among the image datasets, it was difficult to find correlations between different X-ray tube currents or image reconstruction filters that explained the differences. The objective observation of voxel intensity distribution may contribute to the determination of the binarization threshold for 3D model creation. MDPI 2023-03-01 /pmc/articles/PMC10000442/ /pubmed/36900065 http://dx.doi.org/10.3390/diagnostics13050921 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kamio, Takashi
Kawai, Taisuke
CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title_full CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title_fullStr CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title_full_unstemmed CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title_short CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
title_sort cbct images to an stl model: exploring the “critical factors” to binarization thresholds in stl data creation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000442/
https://www.ncbi.nlm.nih.gov/pubmed/36900065
http://dx.doi.org/10.3390/diagnostics13050921
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