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The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing
Virtual reality surgical simulation of temporal bone surgery requires digitized models of the full anatomical region in high quality and colour information to allow realistic texturization. Existing datasets which are usually based on microCT imaging are unable to fulfil these requirements as per th...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326113/ https://www.ncbi.nlm.nih.gov/pubmed/30620342 http://dx.doi.org/10.1038/sdata.2018.297 |
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author | Sieber, Daniel Erfurt, Peter John, Samuel Santos, Gabriel Ribeiro Dos Schurzig, Daniel Sørensen, Mads Sølvsten Lenarz, Thomas |
author_facet | Sieber, Daniel Erfurt, Peter John, Samuel Santos, Gabriel Ribeiro Dos Schurzig, Daniel Sørensen, Mads Sølvsten Lenarz, Thomas |
author_sort | Sieber, Daniel |
collection | PubMed |
description | Virtual reality surgical simulation of temporal bone surgery requires digitized models of the full anatomical region in high quality and colour information to allow realistic texturization. Existing datasets which are usually based on microCT imaging are unable to fulfil these requirements as per the limited specimen size, and lack of colour information. The OpenEar Dataset provides a library consisting of eight three-dimensional models of the human temporal bone to enable surgical training including colour data. Each dataset is based on a combination of multimodal imaging including Cone Beam Computed Tomography (CBCT) and micro-slicing. 3D reconstruction of micro-slicing images and subsequent registration to CBCT images allowed for relatively efficient multimodal segmentation of inner ear compartments, middle ear bones, tympanic membrane, relevant nerve structures, blood vessels and the temporal bone. Raw data from the experiment as well as voxel data and triangulated models from the segmentation are provided in full for use in surgical simulators or any other application which relies on high quality models of the human temporal bone. |
format | Online Article Text |
id | pubmed-6326113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-63261132019-01-10 The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing Sieber, Daniel Erfurt, Peter John, Samuel Santos, Gabriel Ribeiro Dos Schurzig, Daniel Sørensen, Mads Sølvsten Lenarz, Thomas Sci Data Data Descriptor Virtual reality surgical simulation of temporal bone surgery requires digitized models of the full anatomical region in high quality and colour information to allow realistic texturization. Existing datasets which are usually based on microCT imaging are unable to fulfil these requirements as per the limited specimen size, and lack of colour information. The OpenEar Dataset provides a library consisting of eight three-dimensional models of the human temporal bone to enable surgical training including colour data. Each dataset is based on a combination of multimodal imaging including Cone Beam Computed Tomography (CBCT) and micro-slicing. 3D reconstruction of micro-slicing images and subsequent registration to CBCT images allowed for relatively efficient multimodal segmentation of inner ear compartments, middle ear bones, tympanic membrane, relevant nerve structures, blood vessels and the temporal bone. Raw data from the experiment as well as voxel data and triangulated models from the segmentation are provided in full for use in surgical simulators or any other application which relies on high quality models of the human temporal bone. Nature Publishing Group 2019-01-08 /pmc/articles/PMC6326113/ /pubmed/30620342 http://dx.doi.org/10.1038/sdata.2018.297 Text en Copyright © 2019, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Sieber, Daniel Erfurt, Peter John, Samuel Santos, Gabriel Ribeiro Dos Schurzig, Daniel Sørensen, Mads Sølvsten Lenarz, Thomas The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title | The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title_full | The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title_fullStr | The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title_full_unstemmed | The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title_short | The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing |
title_sort | openear library of 3d models of the human temporal bone based on computed tomography and micro-slicing |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326113/ https://www.ncbi.nlm.nih.gov/pubmed/30620342 http://dx.doi.org/10.1038/sdata.2018.297 |
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