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A multiscale imaging and modelling dataset of the human inner ear
Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in stud...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5604133/ https://www.ncbi.nlm.nih.gov/pubmed/28925991 http://dx.doi.org/10.1038/sdata.2017.132 |
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author | Gerber, Nicolas Reyes, Mauricio Barazzetti, Livia Kjer, Hans Martin Vera, Sergio Stauber, Martin Mistrik, Pavel Ceresa, Mario Mangado, Nerea Wimmer, Wilhelm Stark, Thomas Paulsen, Rasmus R. Weber, Stefan Caversaccio, Marco Ballester, Miguel A. González |
author_facet | Gerber, Nicolas Reyes, Mauricio Barazzetti, Livia Kjer, Hans Martin Vera, Sergio Stauber, Martin Mistrik, Pavel Ceresa, Mario Mangado, Nerea Wimmer, Wilhelm Stark, Thomas Paulsen, Rasmus R. Weber, Stefan Caversaccio, Marco Ballester, Miguel A. González |
author_sort | Gerber, Nicolas |
collection | PubMed |
description | Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in studies conducted with few samples. To assist the cochlear research community, a large collection of human temporal bone images is being made available. This data descriptor, therefore, describes a rich set of image volumes acquired using cone beam computed tomography and micro-CT modalities, accompanied by manual delineations of the cochlea and sub-compartments, a statistical shape model encoding its anatomical variability, and data for electrode insertion and electrical simulations. This data makes an important asset for future studies in need of high-resolution data and related statistical data objects of the cochlea used to leverage scientific hypotheses. It is of relevance to anatomists, audiologists, computer scientists in the different domains of image analysis, computer simulations, imaging formation, and for biomedical engineers designing new strategies for cochlear implantations, electrode design, and others. |
format | Online Article Text |
id | pubmed-5604133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-56041332017-09-28 A multiscale imaging and modelling dataset of the human inner ear Gerber, Nicolas Reyes, Mauricio Barazzetti, Livia Kjer, Hans Martin Vera, Sergio Stauber, Martin Mistrik, Pavel Ceresa, Mario Mangado, Nerea Wimmer, Wilhelm Stark, Thomas Paulsen, Rasmus R. Weber, Stefan Caversaccio, Marco Ballester, Miguel A. González Sci Data Data Descriptor Understanding the human inner ear anatomy and its internal structures is paramount to advance hearing implant technology. While the emergence of imaging devices allowed researchers to improve understanding of intracochlear structures, the difficulties to collect appropriate data has resulted in studies conducted with few samples. To assist the cochlear research community, a large collection of human temporal bone images is being made available. This data descriptor, therefore, describes a rich set of image volumes acquired using cone beam computed tomography and micro-CT modalities, accompanied by manual delineations of the cochlea and sub-compartments, a statistical shape model encoding its anatomical variability, and data for electrode insertion and electrical simulations. This data makes an important asset for future studies in need of high-resolution data and related statistical data objects of the cochlea used to leverage scientific hypotheses. It is of relevance to anatomists, audiologists, computer scientists in the different domains of image analysis, computer simulations, imaging formation, and for biomedical engineers designing new strategies for cochlear implantations, electrode design, and others. Nature Publishing Group 2017-09-19 /pmc/articles/PMC5604133/ /pubmed/28925991 http://dx.doi.org/10.1038/sdata.2017.132 Text en Copyright © 2017, 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 Gerber, Nicolas Reyes, Mauricio Barazzetti, Livia Kjer, Hans Martin Vera, Sergio Stauber, Martin Mistrik, Pavel Ceresa, Mario Mangado, Nerea Wimmer, Wilhelm Stark, Thomas Paulsen, Rasmus R. Weber, Stefan Caversaccio, Marco Ballester, Miguel A. González A multiscale imaging and modelling dataset of the human inner ear |
title | A multiscale imaging and modelling dataset of the human inner ear |
title_full | A multiscale imaging and modelling dataset of the human inner ear |
title_fullStr | A multiscale imaging and modelling dataset of the human inner ear |
title_full_unstemmed | A multiscale imaging and modelling dataset of the human inner ear |
title_short | A multiscale imaging and modelling dataset of the human inner ear |
title_sort | multiscale imaging and modelling dataset of the human inner ear |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5604133/ https://www.ncbi.nlm.nih.gov/pubmed/28925991 http://dx.doi.org/10.1038/sdata.2017.132 |
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