Mukund Balasubramanian did something with barycentric coordinates to 
solve this problem, but I don't know whether he ended up publishing it 
or not.


On 03/30/2017 06:19 PM, Burke Rosen wrote:
> I am interested in finding the distance between two vertices along the 
> cortical surface.
>
> So far I have used two methods:
>
> (1) Compute the shortest path with a variant of Dijkstra's algorithm 
> on the white surface.
>
> (2) Compute the great circle distance on the sphere surface.
> (as done by Risk et.al <http://et.al>. 2016 Neuroimage)
>
> Method (1) is slow and will tend to overestimate distances as the path 
> only goes along mesh edges.
>
> Method (2) is very fast and gives a true geodesic but gives a scaled 
> result because the radius of  sphere surface is arbitrary; also this 
> method is subject to distortions introduced by the inflation algorithm.
>
> My current strategy is to perform a linear regression between the 
> triangle face areas of the sphere and white surfaces. And then apply 
> the coefficients to the sphere surface diameter before calculating 
> geodesic distances. This yields a distance matrix with a similar 
> pattern to the Method (1) at about 62% scale. That scale seems like it 
> might be reasonable. However, the regression only explains ~58% of the 
> variance. My hunch is that the rest is due to inflation distortions.
>
> Is there a better way of scaling the sphere surface? Or a way to 
> inflate in such a way that inter-vertex distances are preserved? Or, 
> more generally, what is a good method of computing geodesic distances 
> on freesurfer surfaces.
>
> Thank you,
>
> Burke Rosen
>
>
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