A stochastic model for studying the laminar structure of cortex from MRI

Patrick Ernest Barta, Michael I. Miller, Anqi Qiu

Research output: Contribution to journalArticle

Abstract

The human cerebral cortex is a laminar structure about 3 mm thick, and is easily visualized with current magnetic resonance (MR) technology. The thickness of the cortex varies locally by region, and is likely to be influenced by such factors as development, disease and aging. Thus, accurate measurements of local cortical thickness are likely to be of interest to other researchers. We develop a parametric stochastic model relating the laminar structure of local regions of the cerebral cortex to MR image data. Parameters of the model include local thickness, and statistics describing white, gray and cerebrospinal fluid (CSF) image intensity values as a function of the normal distance from the center of a voxel to a local coordinate system anchored at the gray/white matter interface. Our fundamental data object, the intensity-distance histogram (IDH), is a two-dimensional (2-D) generalization of the conventional 1-D image intensity histogram, which indexes voxels not only by their intensity value, but also by their normal distance to the gray/white interface. We model the IDH empirically as a marked Poisson process with marking process a Gaussian random field model of image intensity indexed against normal distance. In this paper, we relate the parameters of the IDH model to the local geometry of the cortex. A maximum-likelihood framework estimates the parameters of the model from the data. Here, we show estimates of these parameters for 10 volumes in the posterior cingulate, and 6 volumes in the anterior and posterior banks of the central sulcus. The accuracy of the estimates is quantified via Cramer-Rao bounds. We believe that this relatively crude model can be extended in a straightforward fashion to other biologically and theoretically interesting problems such as segmentation, surface area estimation, and estimating the thickness distribution in a variety of biologically relevant contexts.

Original languageEnglish (US)
Pages (from-to)728-742
Number of pages15
JournalIEEE Transactions on Medical Imaging
Volume24
Issue number6
DOIs
StatePublished - Jun 2005

Fingerprint

Stochastic models
Cerebral Cortex
Magnetic resonance imaging
Magnetic Resonance Spectroscopy
Likelihood Functions
Gyrus Cinguli
Cerebrospinal Fluid
Research Personnel
Magnetic resonance
Technology
Cerebrospinal fluid
Cramer-Rao bounds
Maximum likelihood
Aging of materials
Statistics
Geometry
White Matter
Gray Matter

Keywords

  • Cortical thickness
  • Intensity-distance histogram (IDH)
  • Normal distance
  • Partial volume effect

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

A stochastic model for studying the laminar structure of cortex from MRI. / Barta, Patrick Ernest; Miller, Michael I.; Qiu, Anqi.

In: IEEE Transactions on Medical Imaging, Vol. 24, No. 6, 06.2005, p. 728-742.

Research output: Contribution to journalArticle

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