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This research aims to explore the mapping of retinal surfaces to the primary visual cortex using computer-aided techniques.

Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm

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This research aims to explore the mapping of retinal surfaces to the primary visual cortex using computer-aided techniques.
Developed an algorithm for unfolding and flattening cortical surfaces.
Measured differential geometric characteristics of cortical surfaces.
Created models illustrating images mapped to primate striate cortex.
The algorithm successfully flattened cortical surfaces, optimizing visualization.
Differential geometric measurements provided insights into the structures of brain images.
Models indicated complex representations of sensory information in the striate cortex.

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Randomized trial demonstrates an optimal algorithm for cortical surface flattening in neuroanatomy, indicating new possibilities for image mapping.

Schwartz et al. (1986) studied this question.

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Randomized trial demonstrates an optimal algorithm for cortical surface flattening in neuroanatomy, indicating new possibilities for image mapping.