Skip to main content

Research Repository

Advanced Search

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

Bastiani, Matteo; Oros-Peusquens, Ana-Maria; Seehaus, Arne; Brenner, Daniel; Möllenhoff, Klaus; Celik, Avdo; Felder, Jörg; Bratzke, Hansjürgen; Shah, Nadim J.; Galuske, Ralf; Goebel, Rainer; Roebroeck, Alard

Authors

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



Abstract

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.

Journal Article Type Article
Publication Date Nov 10, 2016
Journal Frontiers in Neuroscience
Print ISSN 1662-4548
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 10
Article Number 487
APA6 Citation Bastiani, M., Oros-Peusquens, A., Seehaus, A., Brenner, D., Möllenhoff, K., Celik, A., …Roebroeck, A. (2016). Automatic segmentation of human cortical layer-complexes and architectural areas using ex vivo diffusion MRI and its validation. Frontiers in Neuroscience, 10, https://doi.org/10.3389/fnins.2016.00487
DOI https://doi.org/10.3389/fnins.2016.00487
Publisher URL https://www.frontiersin.org/articles/10.3389/fnins.2016.00487/full

Files





You might also like



Downloadable Citations

;