Automatic Segmentation of Human Cortical Layer-Complexes and Architectural Areas Using Ex vivo Diffusion MRI and Its Validation

Matteo Bastiani, Ana-Maria Oros-Peusquens, Arne Seehaus, Daniel Brenner, Klaus Mollenhoff, Avdo Celik, Jeorg Felder, Hansjuergen Bratzke, Nadim J. Shah, Ralf Galuske, Rainer Goebel, Alard Roebroeck*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.
Original languageEnglish
Article number487
JournalFrontiers in Neuroscience
Volume10
DOIs
Publication statusPublished - 10 Nov 2016

Keywords

  • diffusion MRI
  • cortical layers and areas
  • ultra-high field MRI
  • MR-based histology
  • histological validation

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