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7 Tesla MRI of the ex vivo human brain at 100 micron resolution
We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner a...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821740/ https://www.ncbi.nlm.nih.gov/pubmed/31666530 http://dx.doi.org/10.1038/s41597-019-0254-8 |
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author | Edlow, Brian L. Mareyam, Azma Horn, Andreas Polimeni, Jonathan R. Witzel, Thomas Tisdall, M. Dylan Augustinack, Jean C. Stockmann, Jason P. Diamond, Bram R. Stevens, Allison Tirrell, Lee S. Folkerth, Rebecca D. Wald, Lawrence L. Fischl, Bruce van der Kouwe, Andre |
author_facet | Edlow, Brian L. Mareyam, Azma Horn, Andreas Polimeni, Jonathan R. Witzel, Thomas Tisdall, M. Dylan Augustinack, Jean C. Stockmann, Jason P. Diamond, Bram R. Stevens, Allison Tirrell, Lee S. Folkerth, Rebecca D. Wald, Lawrence L. Fischl, Bruce van der Kouwe, Andre |
author_sort | Edlow, Brian L. |
collection | PubMed |
description | We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 µm isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of scan time (25 hours per flip angle), allowing derivation of synthesized FLASH volumes. This dataset provides an unprecedented view of the three-dimensional neuroanatomy of the human brain. To optimize the utility of this resource, we warped the dataset into standard stereotactic space. We now distribute the dataset in both native space and stereotactic space to the academic community via multiple platforms. We envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance understanding of human brain anatomy in health and disease. |
format | Online Article Text |
id | pubmed-6821740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68217402019-11-07 7 Tesla MRI of the ex vivo human brain at 100 micron resolution Edlow, Brian L. Mareyam, Azma Horn, Andreas Polimeni, Jonathan R. Witzel, Thomas Tisdall, M. Dylan Augustinack, Jean C. Stockmann, Jason P. Diamond, Bram R. Stevens, Allison Tirrell, Lee S. Folkerth, Rebecca D. Wald, Lawrence L. Fischl, Bruce van der Kouwe, Andre Sci Data Data Descriptor We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 µm isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of scan time (25 hours per flip angle), allowing derivation of synthesized FLASH volumes. This dataset provides an unprecedented view of the three-dimensional neuroanatomy of the human brain. To optimize the utility of this resource, we warped the dataset into standard stereotactic space. We now distribute the dataset in both native space and stereotactic space to the academic community via multiple platforms. We envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance understanding of human brain anatomy in health and disease. Nature Publishing Group UK 2019-10-30 /pmc/articles/PMC6821740/ /pubmed/31666530 http://dx.doi.org/10.1038/s41597-019-0254-8 Text en © The Author(s) 2019 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 associated with this article. |
spellingShingle | Data Descriptor Edlow, Brian L. Mareyam, Azma Horn, Andreas Polimeni, Jonathan R. Witzel, Thomas Tisdall, M. Dylan Augustinack, Jean C. Stockmann, Jason P. Diamond, Bram R. Stevens, Allison Tirrell, Lee S. Folkerth, Rebecca D. Wald, Lawrence L. Fischl, Bruce van der Kouwe, Andre 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title | 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title_full | 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title_fullStr | 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title_full_unstemmed | 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title_short | 7 Tesla MRI of the ex vivo human brain at 100 micron resolution |
title_sort | 7 tesla mri of the ex vivo human brain at 100 micron resolution |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821740/ https://www.ncbi.nlm.nih.gov/pubmed/31666530 http://dx.doi.org/10.1038/s41597-019-0254-8 |
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