Gyrification/Addendum: Difference between revisions

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{{subpages}}
{{subpages}}
Commonly used measures of the exent of cortical folding include:
== Quantitative measures of gyrification ==
Commonly used measures of the exent of cortical folding include<ref name=Rodriguez-carranza2008>{{citation
| last1 = Rodriguez-Carranza | first1 = C.E.
| last2 = Mukherjee | first2 = P.
| last3 = Vigneron | first3 = D.
| last4 = Barkovich | first4 = J.
| last5 = Studholme | first5 = C.
| year = 2008
| title = A framework for in vivo quantification of regional brain folding in premature neonates
| journal = Neuroimage
| volume = 41
| pages = 462
| doi = 10.1016/j.neuroimage.2008.01.008
| url = http://linkinghub.elsevier.com/retrieve/pii/S1053811908000311
}}</ref><ref name=Pienaar2008>{{citation
| last1 = Pienaar | first1 = R.
| last2 = Fischl | first2 = B.
| last3 = Caviness | first3 = V.
| last4 = Makris | first4 = N.
| last5 = Grant | first5 = P.E.
| year = 2008
| title = A methodology for analyzing curvature in the developing brain from preterm to adult
| journal = International Journal of Imaging Systems and Technology
| volume = 18
| issue = 1
| pages = 42–68
| doi = 10.1002/ima.20138
| url = http://www3.interscience.wiley.com/journal/119877321/abstract
}}</ref>:
*[[L2 norm|<math> L^2 norms</math>]]:
*[[L2 norm|<math> L^2 norms</math>]]:
**<math>LN_G = \tfrac{1}{4\pi} \textstyle \sqrt{\sum_A K^2}</math>, with <math>K = k_1 k_2</math> being the [[Gaussian curvature]], computed from the two [[principal curvature]]s <math>k_1</math> and <math>k_2</math>
**<math>LN_G = \tfrac{1}{4\pi} \textstyle \sqrt{\sum_A K^2}</math>, with <math>K = k_1 k_2</math> being the [[Gaussian curvature]], computed from the two [[principal curvature]]s <math>k_1</math> and <math>k_2</math>
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*Intrinsic curvature index
*Intrinsic curvature index
**<math>ICI =\tfrac{1}{4\pi} \textstyle \sum_A K^+</math>, with <math>K^+</math> being the positive Gaussian curvature
**<math>ICI =\tfrac{1}{4\pi} \textstyle \sum_A K^+</math>, with <math>K^+</math> being the positive Gaussian curvature
 
*Curvedness
**<math>C =\sqrt{\tfrac{k_1^2+k_2^2}{2}}</math>
*Sharpness of folding
**<math>S =(k_1-k_2)^2</math>
*Bending energy
**<math>E_b =\int_A{(k_1+k_2)}^2dA</math>
*Willmore energy
**<math>E_W =\int_A{(k_1-k_2)}^2dA =\int_A{H}^2dA - \int_A{K}dA </math>
*Gyrification index
*Gyrification index
**<math>GI(n) =\tfrac{A(n)_{pial}}{A(n)_{gc}}</math>, with <math>n</math> indicating the number of the slice, and <math>A(n)_{pial}</math> and <math>A(n)_{gc}</math> being the [[pia mater|pial]] surface area in that slice and the surface area of the boundary between gray matter and cerebrospinal fluid, respectively
**<math>GI_{slice} (n) =\tfrac{A(n)_{outer}}{A(n)_{inner}}</math>, with <math>n</math> indicating the number of the slice, and <math>A(n)_{outer}</math> and <math>A(n)_{inner}</math> being the outer and inner cortical [[contour]] in that slice. Anatomically, the inner contour can be thought of as representing the [[pia mater]], the outer one the [[arachnoid mater]]. The latter correspondence is rough, since the arachnoid also encloses [[venous sinuse]]s.
**<math>GI_{mesh} (n) =\tfrac{A(n)_{outer}}{A(n)_{inner}}</math>, with <math>n</math> indicating the number of the region, and <math>A(n)_{outer}</math> and <math>A(n)_{inner}</math> being the outer and inner cortical [[surface area]] in that region. The anatomical correspondences apply equally to the slice-based and regional definitions.
*Gyrification-White index
*Gyrification-White index
**<math>GWI =\tfrac{A_{gw}}{A_{gc}}</math>, with <math>A_{gw}</math> being the surface area of the boundary between gray matter and white matter  
**<math>GWI =\tfrac{A_{gw}}{A_{gc}}</math>, with <math>A_{gw}</math> being the surface area of the boundary between grey matter and white matter  
*White matter folding
*White matter folding
**<math>WMF =\tfrac{A_{gw}}{{V_w}^{2/3}}</math>, with <math>V_w</math> being the volume of the white matter
**<math>WMF =\tfrac{A_{gw}}{{V_w}^{2/3}}</math>, with <math>V_w</math> being the volume of the white matter
*Cortical complexity
*Cortical complexity
*Fractal dimension
*Fractal dimension
*Global gyrification index
*Local gyrification index
*Shape index
*Shape index
*Curvedness
*Roundness
*Roundness
**<math>Rn =\tfrac{A}{^3\sqrt{36 \pi V^2}}</math>
**<math>RN =\tfrac{A}{^3\sqrt{36 \pi V^2}}</math>
 
== References ==
{{reflist}}

Latest revision as of 10:27, 1 April 2024

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This addendum is a continuation of the article Gyrification.

Quantitative measures of gyrification

Commonly used measures of the exent of cortical folding include[1][2]:

  • :
    • , with being the Gaussian curvature, computed from the two principal curvatures and
    • , with being the Mean curvature and the area of the surface in question
  • Folding index
    • , with
  • Intrinsic curvature index
    • , with being the positive Gaussian curvature
  • Curvedness
  • Sharpness of folding
  • Bending energy
  • Willmore energy
  • Gyrification index
    • , with indicating the number of the slice, and and being the outer and inner cortical contour in that slice. Anatomically, the inner contour can be thought of as representing the pia mater, the outer one the arachnoid mater. The latter correspondence is rough, since the arachnoid also encloses venous sinuses.
    • , with indicating the number of the region, and and being the outer and inner cortical surface area in that region. The anatomical correspondences apply equally to the slice-based and regional definitions.
  • Gyrification-White index
    • , with being the surface area of the boundary between grey matter and white matter
  • White matter folding
    • , with being the volume of the white matter
  • Cortical complexity
  • Fractal dimension
  • Shape index
  • Roundness

References

  1. Rodriguez-Carranza, C.E.; P. Mukherjee & D. Vigneron et al. (2008), "A framework for in vivo quantification of regional brain folding in premature neonates", Neuroimage 41: 462, DOI:10.1016/j.neuroimage.2008.01.008
  2. Pienaar, R.; B. Fischl & V. Caviness et al. (2008), "A methodology for analyzing curvature in the developing brain from preterm to adult", International Journal of Imaging Systems and Technology 18 (1): 42–68, DOI:10.1002/ima.20138