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Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks
The presented data set consists of images, labels and surface models of 23 human bony labyrinths. For each specimen clinical computed tomography (CT) and co-registered high-resolution micro-CT images were acquired. Using the images, the bony labyrinth was segmented and 3D surface models were generat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864122/ https://www.ncbi.nlm.nih.gov/pubmed/31763421 http://dx.doi.org/10.1016/j.dib.2019.104782 |
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author | Wimmer, Wilhelm Anschuetz, Lukas Weder, Stefan Wagner, Franca Delingette, Hervé Caversaccio, Marco |
author_facet | Wimmer, Wilhelm Anschuetz, Lukas Weder, Stefan Wagner, Franca Delingette, Hervé Caversaccio, Marco |
author_sort | Wimmer, Wilhelm |
collection | PubMed |
description | The presented data set consists of images, labels and surface models of 23 human bony labyrinths. For each specimen clinical computed tomography (CT) and co-registered high-resolution micro-CT images were acquired. Using the images, the bony labyrinth was segmented and 3D surface models were generated. Each specimen is accompanied by a description file containing the coordinates of anatomical landmarks and the corresponding cochlear coordinate system. The data set can be used to study the morphology of the inner ear or to evaluate segmentation algorithm as used for the preoperative planning of surgical procedures such as cochlear implantation. |
format | Online Article Text |
id | pubmed-6864122 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68641222019-11-22 Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks Wimmer, Wilhelm Anschuetz, Lukas Weder, Stefan Wagner, Franca Delingette, Hervé Caversaccio, Marco Data Brief Medicine and Dentistry The presented data set consists of images, labels and surface models of 23 human bony labyrinths. For each specimen clinical computed tomography (CT) and co-registered high-resolution micro-CT images were acquired. Using the images, the bony labyrinth was segmented and 3D surface models were generated. Each specimen is accompanied by a description file containing the coordinates of anatomical landmarks and the corresponding cochlear coordinate system. The data set can be used to study the morphology of the inner ear or to evaluate segmentation algorithm as used for the preoperative planning of surgical procedures such as cochlear implantation. Elsevier 2019-11-09 /pmc/articles/PMC6864122/ /pubmed/31763421 http://dx.doi.org/10.1016/j.dib.2019.104782 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Medicine and Dentistry Wimmer, Wilhelm Anschuetz, Lukas Weder, Stefan Wagner, Franca Delingette, Hervé Caversaccio, Marco Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title | Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title_full | Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title_fullStr | Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title_full_unstemmed | Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title_short | Human bony labyrinth dataset: Co-registered CT and micro-CT images, surface models and anatomical landmarks |
title_sort | human bony labyrinth dataset: co-registered ct and micro-ct images, surface models and anatomical landmarks |
topic | Medicine and Dentistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864122/ https://www.ncbi.nlm.nih.gov/pubmed/31763421 http://dx.doi.org/10.1016/j.dib.2019.104782 |
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