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Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset

The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These...

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Autores principales: Kulaga-Yoskovitz, Jessie, Bernhardt, Boris C., Hong, Seok-Jun, Mansi, Tommaso, Liang, Kevin E., van der Kouwe, Andre J.W., Smallwood, Jonathan, Bernasconi, Andrea, Bernasconi, Neda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640139/
https://www.ncbi.nlm.nih.gov/pubmed/26594378
http://dx.doi.org/10.1038/sdata.2015.59
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author Kulaga-Yoskovitz, Jessie
Bernhardt, Boris C.
Hong, Seok-Jun
Mansi, Tommaso
Liang, Kevin E.
van der Kouwe, Andre J.W.
Smallwood, Jonathan
Bernasconi, Andrea
Bernasconi, Neda
author_facet Kulaga-Yoskovitz, Jessie
Bernhardt, Boris C.
Hong, Seok-Jun
Mansi, Tommaso
Liang, Kevin E.
van der Kouwe, Andre J.W.
Smallwood, Jonathan
Bernasconi, Andrea
Bernasconi, Neda
author_sort Kulaga-Yoskovitz, Jessie
collection PubMed
description The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These approaches, however, demand time-consuming manual segmentation that relies heavily on anatomical expertise. Here, we share manual labels and associated high-resolution MRI data (MNI-HISUB25; submillimetric T1- and T2-weighted images, detailed sequence information, and stereotaxic probabilistic anatomical maps) based on 25 healthy subjects. Data were acquired on a widely available 3 Tesla MRI system using a 32 phased-array head coil. The protocol divided the hippocampal formation into three subregions: subicular complex, merged Cornu Ammonis 1, 2 and 3 (CA1-3) subfields, and CA4-dentate gyrus (CA4-DG). Segmentation was guided by consistent intensity and morphology characteristics of the densely myelinated molecular layer together with few geometry-based boundaries flexible to overall mesiotemporal anatomy, and achieved excellent intra-/inter-rater reliability (Dice index ≥90/87%). The dataset can inform neuroimaging assessments of the mesiotemporal lobe and help to develop segmentation algorithms relevant for basic and clinical neurosciences.
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spelling pubmed-46401392015-11-20 Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset Kulaga-Yoskovitz, Jessie Bernhardt, Boris C. Hong, Seok-Jun Mansi, Tommaso Liang, Kevin E. van der Kouwe, Andre J.W. Smallwood, Jonathan Bernasconi, Andrea Bernasconi, Neda Sci Data Data Descriptor The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These approaches, however, demand time-consuming manual segmentation that relies heavily on anatomical expertise. Here, we share manual labels and associated high-resolution MRI data (MNI-HISUB25; submillimetric T1- and T2-weighted images, detailed sequence information, and stereotaxic probabilistic anatomical maps) based on 25 healthy subjects. Data were acquired on a widely available 3 Tesla MRI system using a 32 phased-array head coil. The protocol divided the hippocampal formation into three subregions: subicular complex, merged Cornu Ammonis 1, 2 and 3 (CA1-3) subfields, and CA4-dentate gyrus (CA4-DG). Segmentation was guided by consistent intensity and morphology characteristics of the densely myelinated molecular layer together with few geometry-based boundaries flexible to overall mesiotemporal anatomy, and achieved excellent intra-/inter-rater reliability (Dice index ≥90/87%). The dataset can inform neuroimaging assessments of the mesiotemporal lobe and help to develop segmentation algorithms relevant for basic and clinical neurosciences. Nature Publishing Group 2015-11-10 /pmc/articles/PMC4640139/ /pubmed/26594378 http://dx.doi.org/10.1038/sdata.2015.59 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
spellingShingle Data Descriptor
Kulaga-Yoskovitz, Jessie
Bernhardt, Boris C.
Hong, Seok-Jun
Mansi, Tommaso
Liang, Kevin E.
van der Kouwe, Andre J.W.
Smallwood, Jonathan
Bernasconi, Andrea
Bernasconi, Neda
Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title_full Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title_fullStr Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title_full_unstemmed Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title_short Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset
title_sort multi-contrast submillimetric 3 tesla hippocampal subfield segmentation protocol and dataset
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640139/
https://www.ncbi.nlm.nih.gov/pubmed/26594378
http://dx.doi.org/10.1038/sdata.2015.59
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