[img]https://i.stack.imgur.com/gcNFn.png[/img]
This surface is too densely tessellated for me, so I subsample it to get a coarser surface. To do this, I used Matlab's reducepatch function. This works pretty well:
[code]https://i.stack.imgur.com/U6sVm.png[/code]
White matter subsampled
Unfortunately, the coloring is based on a variable called sulcal_depth, which is defined for every vertex of my tessellated surface. So I need to retain sulcal depth information only from the vertices which remain after subsampling. Essentially, I need reducepatch to give me not just the subsampled version of the surface, but also the indices of vertex points that it retained. If I know the preserved indices, I can just index my sulcal_depth variable to get the new depth map.
Currently, I'm doing this as follows (this is also how I colored the subsampled version above): [code]function indices = compute_reduced_indices(before, after)
%% Function to compute the indices of vertices preserved during an operation of
% reducepatch. This allows you to use reducepatch to subsample a surface and
% re-compute an original signal on the vertices for the new subsampled mesh
indices = zeros(length(after), 1);
for i = 1:length(after)
dotprods = (before * after(i, :)') ./ sqrt(sum(before.^2, 2));
[~, indices(i)] = max(dotprods);
end[/code]
But as you might imagine, this is pretty slow, because of the for loop over vertices. I don't have enough memory to vectorize the loop and compute the full dot product matrix in one go.
Is there a smart way to get reducepatch to give me indices, or an alternative approach (with or without reducepatch) that's faster?">
[img]https://i.stack.imgur.com/gcNFn.png[/img]
This surface is too densely tessellated for me, so I subsample it to get a coarser surface. To do this, I used Matlab's reducepatch function. This works pretty well:
[code]https://i.stack.imgur.com/U6sVm.png[/code]
White matter subsampled
Unfortunately, the coloring is based on a variable called sulcal_depth, which is defined for every vertex of my tessellated surface. So I need to retain sulcal depth information only from the vertices which remain after subsampling. Essentially, I need reducepatch to give me not just the subsampled version of the surface, but also the indices of vertex points that it retained. If I know the preserved indices, I can just index my sulcal_depth variable to get the new depth map.
Currently, I'm doing this as follows (this is also how I colored the subsampled version above): [code]function indices = compute_reduced_indices(before, after)
%% Function to compute the indices of vertices preserved during an operation of
% reducepatch. This allows you to use reducepatch to subsample a surface and
% re-compute an original signal on the vertices for the new subsampled mesh
indices = zeros(length(after), 1);
for i = 1:length(after)
dotprods = (before * after(i, :)') ./ sqrt(sum(before.^2, 2));
[~, indices(i)] = max(dotprods);
end[/code]
But as you might imagine, this is pretty slow, because of the for loop over vertices. I don't have enough memory to vectorize the loop and compute the full dot product matrix in one go.
Is there a smart way to get reducepatch to give me indices, or an alternative approach (with or without reducepatch) that's faster?">
[img]https://i.stack.imgur.com/gcNFn.png[/img]
This surface is too densely tessellated for me, so I subsample it to get a coarser surface. To do this, I used Matlab's reducepatch function. This works pretty well:
[code]https://i.stack.imgur.com/U6sVm.png[/code]
White matter subsampled
Unfortunately, the coloring is based on a variable called sulcal_depth, which is defined for every vertex of my tessellated surface. So I need to retain sulcal depth information only from the vertices which remain after subsampling. Essentially, I need reducepatch to give me not just the subsampled version of the surface, but also the indices of vertex points that it retained. If I know the preserved indices, I can just index my sulcal_depth variable to get the new depth map.
Currently, I'm doing this as follows (this is also how I colored the subsampled version above): [code]function indices = compute_reduced_indices(before, after)
%% Function to compute the indices of vertices preserved during an operation of
% reducepatch. This allows you to use reducepatch to subsample a surface and
% re-compute an original signal on the vertices for the new subsampled mesh
indices = zeros(length(after), 1);
for i = 1:length(after)
dotprods = (before * after(i, :)') ./ sqrt(sum(before.^2, 2));
[~, indices(i)] = max(dotprods);
end[/code]
But as you might imagine, this is pretty slow, because of the for loop over vertices. I don't have enough memory to vectorize the loop and compute the full dot product matrix in one go.
Is there a smart way to get reducepatch to give me indices, or an alternative approach (with or without reducepatch) that's faster?">
The Engineering Projects
A lot of Engineering projects and tutorials for the students to help them in their final year projects and semester projects.
I have a very densely tessellated surface which looks like this: White matter dense [img]https://i.stack.imgur.com/gcNFn.png[/img]
This surface is too densely tessellated for me, so I subsample it to get a coarser surface. To do this, I used Matlab's reducepatch function. This works pretty well:
[code]https://i.stack.imgur.com/U6sVm.png[/code]
White matter subsampled
Unfortunately, the coloring is based on a variable called sulcal_depth, which is defined for every vertex of my tessellated surface. So I need to retain sulcal depth information only from the vertices which remain after subsampling. Essentially, I need reducepatch to give me not just the subsampled version of the surface, but also the indices of vertex points that it retained. If I know the preserved indices, I can just index my sulcal_depth variable to get the new depth map.
Currently, I'm doing this as follows (this is also how I colored the subsampled version above): [code]function indices = compute_reduced_indices(before, after)
%% Function to compute the indices of vertices preserved during an operation of
% reducepatch. This allows you to use reducepatch to subsample a surface and
% re-compute an original signal on the vertices for the new subsampled mesh
indices = zeros(length(after), 1);
for i = 1:length(after)
dotprods = (before * after(i, :)') ./ sqrt(sum(before.^2, 2));
[~, indices(i)] = max(dotprods);
end[/code]
But as you might imagine, this is pretty slow, because of the for loop over vertices. I don't have enough memory to vectorize the loop and compute the full dot product matrix in one go.
Is there a smart way to get reducepatch to give me indices, or an alternative approach (with or without reducepatch) that's faster?
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