Abstract
A method for building a statistical shape model of sulci of the human brain cortex is described. The model includes sulcal fundi that are defined on a spherical map of the cortex. The sulcal fundi are first extracted in a semi-automatic way using an extension of the fast marching method. They are then transformed to curves on the unit sphere via a conformal mapping method that maps each cortical point to a point on the unit sphere. The curves that represent sulcal fundi are parameterized with piecewise constant-speed parameterizations. Intermediate points on these curves correspond to sulcal landmarks, which are used to build a point distribution model on the unit sphere. Statistical information of local properties of the sulci, such as curvature and depth, are embedded in the model. Experimental results are presented to show how the models are built.
Acknowledgments
This work was partially supported by NIH grant R01AG14971, NIH contract N01AG32129, NIH grant R01NS37747 and NSF/ERC grant CISST#9731748. The authors would like to acknowledge the Baltimore Longitudinal Study of Aging which provided the datasets.
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Tao, X., Han, X., Rettmann, M.E., Prince, J.L., Davatzikos, C. (2001). Statistical Study on Cortical Sulci of Human Brains. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_51
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