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Journal ArticleDOI

Measuring the thickness of the human cerebral cortex from magnetic resonance images

26 Sep 2000-Proceedings of the National Academy of Sciences of the United States of America (National Academy of Sciences)-Vol. 97, Iss: 20, pp 11050-11055
TL;DR: An automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy is presented.
Abstract: Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test-retest studies, as well as by comparison of cross-subject regional thickness measures with published values.

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Citations
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Journal ArticleDOI
TL;DR: An automated labeling system for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable and may be useful for both morphometric and functional studies of the cerebral cortex.

9,940 citations


Cites background or methods from "Measuring the thickness of the huma..."

  • ...…representations) available on images of the cortex that are Finflated_ (Dale and Sereno, 1993; Dale et al., 1999; Fischl et al., 1999a,b, 2001; Fischl and Dale, 2000); anatomic curvature is visually represented well on inflated images as they provide a view of the brain in which the entire…...

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  • ...First, we have developed the definitions of the regions of interest using curvature based information (i.e., sulcal representations) available on images of the cortex that are Finflated_ (Dale and Sereno, 1993; Dale et al., 1999; Fischl et al., 1999a,b, 2001; Fischl and Dale, 2000); anatomic curvature is visually represented well on inflated images as they provide a view of the brain in which the entire cortical surface is exposed, including the tissue deep in the sulci....

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  • ..., sulcal representations) available on images of the cortex that are Finflated_ (Dale and Sereno, 1993; Dale et al., 1999; Fischl et al., 1999a,b, 2001; Fischl and Dale, 2000); anatomic curvature is visually represented well on inflated images as they provide a view of the brain in which the entire cortical surface is exposed, including the tissue deep in the sulci....

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  • ...The cortical white matter surfaces generated by the steps above were automatically corrected for topological defects (Fischl et al., 2001; Ségonne et al., 2005), and thereafter utilized in a deformation procedure that locates the pial (gray matter) surface of the brain (Fischl and Dale, 2000)....

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  • ...The yellow asterisks on the inflated surface (right) indicate the cortex around the perimeter of the central sulcus that has been Finflated_ and is now visible....

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Journal ArticleDOI
TL;DR: A technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set is presented, comparable in accuracy to manual labeling.
Abstract: We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from a manually labeled training set. This procedure incorporates both geometric information derived from the cortical model, and neuroanatomical convention, as found in the training set. The result is a complete labeling of cortical sulci and gyri. Examples are given from two different training sets generated using different neuroanatomical conventions, illustrating the flexibility of the algorithm. The technique is shown to be comparable in accuracy to manual labeling.

3,880 citations


Cites methods from "Measuring the thickness of the huma..."

  • ...Cortical models were reconstructed for each of the subjects using previously presented techniques, including non-rigid surface-based alignment to a previously constructed spherical atlas (Dale and Sereno, 1993; Dale, Fischl et al., 1999; Fischl, Sereno et al., 1999; Fischl, Sereno et al., 1999; Fischl and Dale, 2000; Fischl, Liu et al., 2001)....

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  • ...For the CMA parcellation we first sample the volumetric labeling onto the reconstructed cortical surface of each subject (Dale, Fischl et al., 1999; Fischl, Sereno et al., 1999; Fischl and Dale, 2000; Fischl, Liu et al., 2001), the subsequent procedures for the two parcellations are identical....

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  • ...14 manual parcellations were then sampled onto the cortical models at the midpoint of the cortical ribbon using the thickness estimates described in (Fischl and Dale, 2000)....

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  • ...For the CMA parcellation we first sample the volumetric labeling onto the reconstructed cortical surface of each subject (Dale et al., 1999; Fischl et al., 1999a, 2001; Fischl and Dale, 2000), the subsequent procedures for the two parcellations are identical....

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  • ...The manual parcellations were then sampled onto the cortical models at the midpoint of the cortical ribbon using the thickness estimates described in Fischl and Dale (2000)....

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Journal ArticleDOI
TL;DR: This is the first study to use a consistent transformation framework to provide a reproducible evaluation of the isolated effect of the similarity metric on optimal template construction and brain labeling, and to quantify the similarity of templates derived from different subgroups.

3,491 citations


Cites methods from "Measuring the thickness of the huma..."

  • ..., 2005), SyN, and Freesurfer (Fischl and Dale, 2000) on whole head data and found that both brain extraction and registration via an “optimal” (groupgenerated) template improve performance....

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  • ...0 (Ardekani et al., 2005), SyN, and Freesurfer (Fischl and Dale, 2000) on whole head data and found that both brain extraction and registration via an “optimal” (groupgenerated) template improve performance....

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Journal ArticleDOI
TL;DR: Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities.

2,679 citations


Cites background from "Measuring the thickness of the huma..."

  • ...We believe that cortex is the best target for two reasons: (1) it is highly folded, allowing dense sampling of 3D space, and, (2) it is very thin (2.5 mm on average; Fischl and Dale, 2000), implying that small alignment errors will generate large changes in the cost function....

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  • ...Cortex has a typical thickness of between 1 and 5 mm (Fischl and Dale, 2000)....

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Journal ArticleDOI
TL;DR: This paper introduces a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points and successfully reduces variability and avoids over-regularization.

1,949 citations


Cites background from "Measuring the thickness of the huma..."

  • ..., 2007), and surface deformation following intensity gradients to optimally place the gray/white and gray/CSF borders at the location where the greatest shift in intensity defines the transition to the other tissue class (Fischl and Dale, 2000)....

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  • ...…correction (Fischl et al., 2001; Ségonne et al., 2007), and surface deformation following intensity gradients to optimally place the gray/white and gray/CSF borders at the location where the greatest shift in intensity defines the transition to the other tissue class (Fischl and Dale, 2000)....

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References
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01 Jan 1994
TL;DR: The Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08.
Abstract: Note: Includes bibliographical references, 3 appendixes and 2 indexes.- Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08

19,881 citations

Journal ArticleDOI
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Abstract: A snake is an energy-minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines and edges. Snakes are active contour models: they lock onto nearby edges, localizing them accurately. Scale-space continuation can be used to enlarge the capture region surrounding a feature. Snakes provide a unified account of a number of visual problems, including detection of edges, lines, and subjective contours; motion tracking; and stereo matching. We have used snakes successfully for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest.

18,095 citations

Journal ArticleDOI
TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.

9,599 citations


"Measuring the thickness of the huma..." refers methods in this paper

  • ...In conjunction with automated surface reconstruction [21-24] and high-resolution surface averaging techniques [25], the measurement of cortical thickness with sub-millimeter accuracy facilitates the use of powerful statistical methods in the investigation of neurodegeneration and recovery....

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  • ...These include methods for constructing [22, 24] and transforming [23] models of the human cerebral cortex, as well as a means for using the pattern of cortical folding derived from these models to drive a high-resolution inter-subject alignment procedure [25]....

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  • ...The surface of the connected white matter voxels is then refined to obtain sub-voxel accuracy in the representation of the gray/white boundary, and subsequently deformed outward to find the pial surface, as described in [22]....

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Book
01 Jan 1988
TL;DR: Direct and Indirect Radiologic Localization Reference System: Basal Brain Line CA-CP Cerebral Structures in Three-Dimensional Space Practical Examples for the Use of the Atlas in Neuroradiologic Examinations Three- Dimensional Atlas of a Human Brain Nomenclature-Abbreviations Anatomic Index Conclusions.
Abstract: Direct and Indirect Radiologic Localization Reference System: Basal Brain Line CA-CP Cerebral Structures in Three-Dimensional Space Practical Examples for the Use of the Atlas in Neuroradiologic Examinations Three-Dimensional Atlas of a Human Brain Nomenclature-Abbreviations Anatomic Index Conclusions.

9,491 citations