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Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images

Three-dimensional reconstruction plays a vital role in assisting doctors and surgeons in diagnosing the healing progress of bone defects. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, this study omits the volume render...

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Autores principales: Chin, Daniel Jie Yuan, Mohamed, Ahmad Sufril Azlan, Shariff, Khairul Anuar, Ab Wahab, Mohd Nadhir, Ishikawa, Kunio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659505/
https://www.ncbi.nlm.nih.gov/pubmed/34883959
http://dx.doi.org/10.3390/s21237955
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author Chin, Daniel Jie Yuan
Mohamed, Ahmad Sufril Azlan
Shariff, Khairul Anuar
Ab Wahab, Mohd Nadhir
Ishikawa, Kunio
author_facet Chin, Daniel Jie Yuan
Mohamed, Ahmad Sufril Azlan
Shariff, Khairul Anuar
Ab Wahab, Mohd Nadhir
Ishikawa, Kunio
author_sort Chin, Daniel Jie Yuan
collection PubMed
description Three-dimensional reconstruction plays a vital role in assisting doctors and surgeons in diagnosing the healing progress of bone defects. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, this study omits the volume rendering methods. Many improvements have been made to surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images and studying the effects of different parameter settings for the improvements. Hence, this study attempts near real-time surface rendering for large medical images. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 5 and mesh simplification reduction factor of 0.1 is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61%, respectively.
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spelling pubmed-86595052021-12-10 Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images Chin, Daniel Jie Yuan Mohamed, Ahmad Sufril Azlan Shariff, Khairul Anuar Ab Wahab, Mohd Nadhir Ishikawa, Kunio Sensors (Basel) Article Three-dimensional reconstruction plays a vital role in assisting doctors and surgeons in diagnosing the healing progress of bone defects. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, this study omits the volume rendering methods. Many improvements have been made to surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images and studying the effects of different parameter settings for the improvements. Hence, this study attempts near real-time surface rendering for large medical images. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 5 and mesh simplification reduction factor of 0.1 is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61%, respectively. MDPI 2021-11-29 /pmc/articles/PMC8659505/ /pubmed/34883959 http://dx.doi.org/10.3390/s21237955 Text en © 2021 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
Chin, Daniel Jie Yuan
Mohamed, Ahmad Sufril Azlan
Shariff, Khairul Anuar
Ab Wahab, Mohd Nadhir
Ishikawa, Kunio
Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title_full Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title_fullStr Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title_full_unstemmed Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title_short Effects of Different Parameter Settings for 3D Data Smoothing and Mesh Simplification on Near Real-Time 3D Reconstruction of High Resolution Bioceramic Bone Void Filling Medical Images
title_sort effects of different parameter settings for 3d data smoothing and mesh simplification on near real-time 3d reconstruction of high resolution bioceramic bone void filling medical images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659505/
https://www.ncbi.nlm.nih.gov/pubmed/34883959
http://dx.doi.org/10.3390/s21237955
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