Hi, I want to reduce the size of a 3D image by averaging the values in 3D. For example if the image is 160*216*176. I wrote the code below to process the image to average the values in every 4*4*4 cube thereby creating a new matrix that is 40*54*44 in size.my code is below
X(1:40)=4;
Y(1:54)=4;
Z(1:44)=4;
A=mat2cell(imagestack_1,[X],[Y],[Z]);
average=cellfun(@mean2,A);
But this shows an error
Error using mat2cell (line 97)
Input arguments, D1 through D3, must sum to each dimension of the input matrix size, [160 216 176].'
Anyone who knows Please guide me!!

3 commentaires

KSSV
KSSV le 14 Mar 2017
What version you are using? Are you sure of size of imagestack_1 ? It worked for me without error on random data of size 160*216*176.
Sandhiya Prakash
Sandhiya Prakash le 14 Mar 2017
I am using MatlabR2016a.
Sandhiya Prakash
Sandhiya Prakash le 14 Mar 2017
I think i must give variable in which 3D image is stored instead of imagestack_1. Kindly guide me.I am new to matlab.

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Walter Roberson
Walter Roberson le 14 Mar 2017

0 votes

You probably had previous values in your X, Y, or Z, making them longer than what would be created with just the above code.

6 commentaires

Example:
imagestack_1 = rand(160, 216, 176);
X = 4 * ones(1,40);
Y = 4 * ones(1,54);
Z = 4 * ones(1,44);
A = mat2cell(imagestack_1, X, Y, Z);
average = cellfun(@mean2, A);
Sandhiya Prakash
Sandhiya Prakash le 14 Mar 2017
Thank you sir..its working.I hav anothe doubt.I am having a 160*216*176 input 3D image. For a given voxel i need to consider 26 neighbouring 3x3x3 patch.(now 27 scalar values)Then consider all 26 neighbouring conventional 3x3x3 patches and compute average intensity for all these neighbouring patches.(So totally i have 53 scalar intensity values).How to perform this?
What is the difference between a "neighbouring 3x3x3 patch" and a "conventional 3x3x3 patch" ?
Is that 53 scalar intensity values per voxel, or 53 total over the entire data?
It would help if you could give the calculation formula in terms of indexes. For example,
conventional = M(I-1:I+1, J-1:J+1, K-1:K+1);
mean_conventional = mean2(conventional);
unconventional = conventional;
unconventional(2,2,2) = []; %center point not included in mean
mean_unconventional = mean2(unconventional);
Sandhiya Prakash
Sandhiya Prakash le 14 Mar 2017
Modifié(e) : Walter Roberson le 14 Mar 2017
Thank U sir! I have a doubt in looping.
my code is
for I=1:160
for J=1:216
for K=1:176
conventional = data(I-1:I+1, J-1:J+1, K-1:K+1);
mean_conventional = mean2(conventional);
unconventional = conventional;
unconventional(2,2,2) = []; %center point not included in mean
mean_unconventional = mean2(unconventional);
end
end
end
but it gives error like,
Subscript indices must either be real positive integers or logicals.
Walter Roberson
Walter Roberson le 14 Mar 2017
The boundary points do not have 27 neighbors. You should either calculate only on the interior, or you should define what you want the boundary calculation to be.
SojM
SojM le 17 Juil 2020
After the resize of the matrix, how to save new 3D matrix as stack of 2D images?

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