The authors implement an algorithm that finds minimal (geodesic)
distances on a three-dimensional polyhedral surface. The algorithm is
intrinsically parallel, in as much as it deals with all nodes
simultaneously, and is simple to implement. Although exponential in
complexity, it can be used with a companion gradient-descent
surface-flattening algorithm that produces an optimal flattening of a
polyhedral surface. Together, these two algorithms have made it
possible to obtain accurate flattening of biological surfaces
consisting of several thousand triangular faces (monkey visual cortex)
by providing a characterization of the distance geometry of these
surfaces. The authors propose this approach as a pragmatic solution to
characterizing the surface geometry of the complex polyhedral surfaces
which are encountered in the cortex of vertebrates