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Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm
March 1986 (vol. 6 no. 3)
pp. 36-44
Eric Schwartz, New York University Medical Center, NSK Institute, and Courant Institute of Mathematical Sciences
Bjorn Merker, New York University Medical Center
In a variety of species including monkeys and humans, the surface of the retina is mapped in an accurate manner to the surface of primary visual cortex. In a real sense there is an image, expressed in the firing density of neurons, impressed on the surface of the brain. The various images found in the brain have complicated natures: They are ``distorted'' by nonlinear map functions, and contain submodality information expressed spatially in the form of columnar systems representing stereo, orientation, motion, and other forms of data. The detailed study of such maps represents a difficult series of problems in the areas of computer graphics, image processing, numerical analysis, and neuroanatomy. This article describes some intial steps in the field of computer-aided neuroanatomy. An algorithm for unfolding and flattening cortical surfaces and a measurement of the differential geometric aspects of these surfaces are presented. Models of the structure of images as they would appear mapped to the surface of primate striate cortex are also shown.

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Citation:
Eric Schwartz, Bjorn Merker, "Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm," IEEE Computer Graphics and Applications, vol. 6, no. 3, pp. 36-44, March 1986, doi:10.1109/MCG.1986.276630
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