Automatic segmentation of human cortical layer-complexes and architectural areas using ex vivo diffusion MRI and its validation

  • Recently, several magnetic resonance imaging contrast mechanisms have been shown to distinguish cortical substructure corresponding to selected cortical layers. Here, we investigate cortical layer and area differentiation by automatized unsupervised clustering of high-resolution diffusion MRI data. Several groups of adjacent layers could be distinguished in human primary motor and premotor cortex. We then used the signature of diffusion MRI signals along cortical depth as a criterion to detect area boundaries and find borders at which the signature changes abruptly. We validate our clustering results by histological analysis of the same tissue. These results confirm earlier studies which show that diffusion MRI can probe layer-specific intracortical fiber organization and, moreover, suggests that it contains enough information to automatically classify architecturally distinct cortical areas. We discuss the strengths and weaknesses of the automatic clustering approach and its appeal for MR-based cortical histology.

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Author:Matteo Bastiani, Ana-Maria Oros-Peusquens, Arne Seehaus, Daniel Brenner, Klaus Möllenhoff, Avdo Celik, Jörg Felder, Hansjürgen Bratzke, Nadim J. Shah, Ralf Galuske, Rainer Goebel, Alard Roebroeck
URN:urn:nbn:de:hebis:30:3-419827
URL:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102896
DOI:https://doi.org/10.3389/fnins.2016.00487
ISSN:1662-453X
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/27891069
Parent Title (English):Frontiers in neuroscience
Publisher:Frontiers Research Foundation
Place of publication:Lausanne
Document Type:Article
Language:English
Year of Completion:2016
Date of first Publication:2016/11/10
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Granting Institution:Johann Wolfgang Goethe-Universität
Release Date:2016/12/01
Tag:MR-based histology; cortical layers and areas; diffusion MRI; histological validation; ultra-high field MRI
Volume:10
Issue:Artikel 487
Page Number:11
Note:
Copyright © 2016 Bastiani, Oros-Peusquens, Seehaus, Brenner, Möllenhoff, Celik, Felder, Bratzke, Shah, Galuske, Goebel and Roebroeck. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) http://creativecommons.org/licenses/by/4.0/ . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
HeBIS-PPN:425295737
Institutes:Medizin / Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0