I've been working on modyfing dicom images so I can later 3d print them. The problem is that once I've modified the individual slices to turn them into an .stl file, the software I'm using (Osirix) prompts an error that asks for volumic data. If I try to render the .stl without modifying it first in MAtlab I get no error message.
I need an example of code for Matlab that can stack 2d images into a 3d surface so I can later import it to an .stl file. Can anyone help me?
One way could be to stack 2D images into a 3D cube of images.
Solution 1.
The following solution is based in the following assumptions:
1) that the size of all 2d images are the same: n1 by n2
2) that you know the number of images (slices): n3
3) that the images are uint8
You could create a 3D cube beforehand with:
allImgs = uint8(zeros(n1, n2, n3));
Then to fill the first slice with aSlice image, do:
allImgs(:, :, 1) = aSlice;
For the second, do:
allImgs(:, :, 2) = anotherSlice;
and so forth.
If you have a function (like getMeASlice())that gets the slices for you, you could efficiently call this from a for loop and fill it up:
for k = 1:n3
allImgs(:, :, k) = getMeASlice(your_params);
end
Solution 2.
You could concatenate slices as you go. Say that you read a slice:
aSlice = imread('cameraman.tif');
and then you later on your code you read another slice and want to stack it to your existing one, you could do:
aSlice = cat(3, aSlice, imread('anotherimage.jpg'));
which concatenates your new slice in the third dimension. And you could keep doing this as long as you need.
However, note the following. Concatenating is very slow compared to preallocating a variable and adding things (populating) such variable. For instance, if you compare the following two scripts, the second one is much slower:
n1=256; n2=256; n3=200;
allImgs = uint8(zeros(n1, n2, n3));
aSlice = imread('cameraman.tif');
tic;
for k=1:n3
allImgs(:,:,1)=aSlice;
end
fprintf(['Total time is: ' num2str(toc) '\n']);
tic;
allImgs=aSlice;
for k=2:n3
allImgs=cat(3, allImgs, aSlice);
end
fprintf(['Total time is: ' num2str(toc) '\n']);
Gives the following in my computer:
Total time is: 0.0085632
Total time is: 0.89103
Let me know if this helps or not.
Related
I have a dataset of n nifti (.nii) images. Ideally, I'd like to be able to get the value of the same voxel/element from each image, and apply a function to the n data points. I'd like to do this for each voxel/element across the whole image, so that I can reconvert the result back into .nii format.
I've used the Tools for NIfTI and ANALYZE image toolbox to load my images:
data(1)=load_nii('C:\file1.nii');
data(2)=load_nii('C:\file2.nii');
...
data(n)=load_nii('C:\filen.nii');
From which I obtain a struct object with each sub-field containing one loaded nifti. Each of these has a subfield 'img' corresponding to the image data I want to work on. The problem comes from trying to select a given xyz within each img field of data(1) to data(n). As I discovered, it isn't possible to select in this way:
data(:).img(x,y,z)
or
data(1:n).img(x,y,z)
because matlab doesn't support it. The contents of the first brackets have to be scalar for the call to work. The solution from googling around seems to be a loop that creates a temporary variable:
for z = 1:nz
for x = 1:nx
for y = 1:ny
for i=1:n;
points(i)=data(i).img(x,y,z);
end
[p1(x,y,z,:),~,p2(x,y,z)] = fit_data(a,points,b);
end
end
end
which works, but takes too long (several days) for a single set of images given the size of nx, ny, nz (several hundred each).
I've been looking for a solution to speed up the code, which I believe depends on removing those loops by vectorisation, preselecting the img fields (via getfield ?)and concatenating them, and applying something like arrayfun/cellfun/structfun, but i'm frankly a bit lost on how to do it. I can only think of ways to pre-select which themselves require loops, which seems to defeat the purpose of the exercise (though a solution with fewer loops, or fewer nested loops at least, might do it), or fun into the same problem that calls like data(:).img(x,y,z) dont work. googling around again is throwing up ways to select and concatenate fields within a struct, or a given field across multiple structs. But I can't find anything for my problem: select an element from a non-scalar sub-field in a sub-struct of a struct object (with the minimum of loops). Finally I need the output to be in the form of a matrix that the toolbox above can turn back into a nifti.
Any and all suggestions, clues, hints and help greatly appreciated!
You can concatenate images as a 4D array and use linear indexes to speed up calculations:
img = cat(4,data.img);
p1 = zeros(nx,ny,nz,n);
p2 = zeros(nx,ny,nz);
sz = ny*nx*nz;
for k = 1 : sz
points = img(k:sz:end);
[p1(k:sz:end),~,p2(k)] = fit_data(a,points,b);
end
I have 200 time points. For each time point, there is an image, the size of which is 40*40 double, corresponds to this time point. For example, image 1 corresponds to time point 1; image k corresponds to time point k (k = 1,2,...,200).
The time points are T = 1:200, with the images named as Image_T, thus Image_1, Image_2 etc.
I want to put all these 200 images together. The final size is 40*40*200 double. The final image looks like fMRI image (fmri_szX = 40, fmri_szY = 40 and fmri_szT = 200). How to achieve that?
Thanks!
Dynamic variables
Note that whilst this is possible, it's considered to be bad programming (see for instance here, or this blog by Loren and even the Mathworks in their documentation tell you not to do this). It would be much better to load your images directly into either a 3D array or a cell structure, avoiding dynamic variable names. I just posted this for completeness; if you ever happen to have to use this solution, you should change to a (cell-) array immediately.
The gist of the linked articles as to why eval is such a bad idea, is that MATLAB can no longer predict what the outcome of the operation will be. For instance A=3*(2:4) is recognised by MATLAB to output a double-array. If you eval stuff, MATLAB can no longer do this. MATLAB is an interpreted language, i.e. each line of code is read then ran, without compiling the entire code beforehand. This means that each time MATLAB encounters eval, it has to stop, evaluate the expression, then check the output, store that, and continue. Most of the speed-engines employed by MATLAB (JIT/MAGMA etc) can't work without predicting the outcome of statements, and will therefore shut down during the eval evaluation, rendering your code very slow.
Also there's a security aspect to the usage of eval. Consider the following:
var1 = 1;
var2 = 2;
var3 = 3;
varnames = {'var1', 'var2; disp(''GOTCHA''); %', 'var3'};
accumvar = [];
for k = 1:numel(varnames)
vname = varnames{k};
disp(['Reading from variable named ' vname]); eval(['accumvar(end+1) = ' vname ';']);
end
Now accumvar will contain the desired variable names. But if you don't set accumvar as output, you might as well not use a disp, but e.g. eval('rm -rf ~/*') which would format your entire disk without even telling you it's doing so.
Loop approach
for ii = 200:-1:1
str = sprintf('Image_%d',ii);
A(:, :, :, ii) = eval(str);
end
This creates your matrix. Note that I let the for loop run backwards, so as to initialise A in its largest size.
Semi-vectorised approach
str = strsplit(sprintf('image_%d ',1:200),' '); % Create all your names
str(end) = []; % Delete the last entry (empty)
%Problem: eval cannot handle cells, loop anyway:
for ii = 200:-1:1
A(:, :, :, ii) = eval(str{ii});
end
eval does not support arrays, so you cannot directly plug the cellarray strin.
Dynamic file names
Despite having a similar title as above, this implies having your file names structured, so in the file browser, and not MATLAB. I'm assuming .jpg files here, but you can add every supported image extension. Also, be sure to have all images in a single folder and no additional images with that extension, or you have to modify the dir() call to include only the desired images.
filenames = dir('*.jpg');
for ii = length(filenames):-1:1
A(:,:,:,ii) = imread(filenames{ii});
end
Images are usually read as m*n*3 files, where m*n is your image size in pixels and the 3 stems from the fact that they're read as RGB by imread. Therefore A is now a 4D matrix, structured as m*n*3*T, where the last index corresponds to the time of the image, and the first three are your image in RGB format.
Since you do not specify how you obtain your 40*40 double, I have left the 4D matrix. Could be you read them and then switch to using a uint16 interpretation of RGB, which is a single number, which would result in a m*n*1*T variable, which you can reduce to a 3D variable by calling A = squeeze(A(:,:,1,:));
I have this program which calculates the realized covariance for each day in my sample but I have some troubles with storing the output in a matrix.
the program is as follows:
for i=1:66:(2071*66)
vec = realized_covariance(datapa(i:i+65),data(i:i+65),datapo(i:i+65),data(i:i+65),'wall','Fixed',fixedInterval,5)
mat(2,4142) = vec
end
Output:
vec =
1.0e-03 *
0.1353 -0.0283
-0.0283 0.0185
Subscripted assignment dimension mismatch.
I have tried various way to store the output in a matrix like defining a matrix on zeroes to store the output in or let the row dimension of the storing matrix be undefined, but nothing seems to do the job.
I would really appreciate an advice on how to tackle this challenge.
I have used a solution which does the job.
I defined a matrix and then filled in all my output one at the time using the following:
A = zeros(0,0) %before loop, only serve to define the storing matrix
A = [A; vec]%after the calculating function, inside the loop.
Actually mat(2,4142) is a single location in a matrix, you can't assign there four values.
You need to define the exact location inside mat every time you want to assign values into it. Try doing it like that:
mat=zeros(2,2142);
for k=1:66:(2071*66)
vec=realized_covariance(datapa(i:i+65),data(i:i+65),datapo(i:i+65),data(i:i+65),'wall','Fixed',fixedInterval,5)
mat(:,[(((k-1)/66)*2)+1 (((k-1)/66)*2)+2])=vec;
end
You're trying to store a 2 x 2 matrix into a single element. I.e. 4 elements on the right hand side, one on the left. That won't fit. See it like this: you have a garage besides your house where 1 car fits. You've got three friends coming over and they also want to park their car inside. That's a problem though, as you've got only space for one. So you have to buy a bigger garage: assign 4 elements on the left (e.g. mat(ii:ii+1,jj:jj+1) = [1 2;3 4]), or use a cell/structure array.
As Steve suggests in a comment below, you can use a 3D matrix quite easily:
counters = 1:66:(2071*66);
mat = zeros(2,2,numel(counters)); %// initialise output matrix
for ii=1:numel(counters)
vec = realized_covariance(datapa(counters(ii):counters(ii+65)),...
data(counters(ii):counters(ii+65)),datapo(counters(ii):counters(ii+65)),...
data(counters(ii):counters(ii+65)),'wall','Fixed',fixedInterval,5)
mat(:,:,ii) = vec; %// store in a 3D matrix
end
Now mat is 3D, with the first two coordinates being your regular output, i.e.e vec, and the last index is the iteration number. So to access the output of iteration 1032 you'd do mat(:,:,1032), possibly with a squeeze around that to make it 2D instead of 3D.
My data is x,y co-ordinates in multiple files
a=dir('*.mat')
b={a(:).name}
to load the filenames in a cell array
How do I use a loop to sequentially load one column of data from each file into consecutive rows of a new/separate array......?
I've been doing it individually using e.g.
Load(example1.mat)
A(:,1)=AB(:,1)
Load(example2.mat)
A(:,2)=AB(:,1)
Load(example3.mat)
A(:,3)=AB(:,1)
Obviously very primitive and time consuming!!
My Matlab skills are weak so any advice gratefully received
Cheers
Many thanks again, I'm still figuring out how to read the code but I used it like this;
a=dir('*.mat');
b={a(:).name};
test1=zeros(numel(b),1765);
for k=1:numel(b) S=load(b{k});
I then used the following code to create a PCA cluster plot
test1(k,:)=S.AB(:,2); end [wcoeff,score,latent,tsquared,explained] = pca(test1,... 'VariableWeights','variance');
c3 = wcoeff(:,1:3) coefforth = inv(diag(std(test1)))*wcoeff; I = c3'*c3 cscores = zscore(test1)*coefforth;
figure() plot(score(:,1),score(:,2),'+') xlabel('1st Principal Component') ylabel('2nd Principal Component') –
I was using 'gname' to label the points on the cluster plot but found that the point were simply labelled from 1 to the number of rows in the array.....I was going to ask you about this but I found out simply through trial and error if I used 'gname(b)' this labels the points with the .names listed in b.....
However the clusterplot starts to look very busy/messy once I have labelled quite a few points so now I am wondering is is possible to extract the filenames into a list by dragging round or selecting a few points, I think it is possible as I have read a few related topics.....but any tips/advice around gname or labelled/extracting labels from clusterplots would be greatly appreciated. Apologies again for my formatting I'm still getting used to this website!!!
Here is a way to do it. Hopefully I got what you wanted correctly :)
The code is commented but please ask any questions if something is unclear.
a=dir('*.mat');
b={a(:).name};
%// Initialize the output array. Here SomeNumber depends on the size of your data in AB.
A = zeros(numel(b),SomeNumber);
%// Loop through each 'example.mat' file
for k = 1:numel(b)
%// ===========
%// Here you could do either of the following:
1)
%// Create a name to load with sprintf. It does not require a or b.
NameToLoad = sprintf('example%i.mat',k);
%// Load the data
S = load(NameToLoad);
2)
%// Load directly from b:
S = load(b{k});
%// ===========
%// Now S is a structure containing every variable from the exampleX.mat file.
%// You can access the data using dot notation.
%// Store the data into rows of A
A(k,:) = S.AB(:,1);
end
Hope that is what you meant!
I am trying to find the difference between two images, using Matlab. The classic built in function that Matlab provides for this is because the two images don't have the same dimensions (The objects in the images are the same, but in the second image other objects are introduced).
And i thought i could use SURF Features to accomplish this.
Here's the code:
source = imread('source.png');
target = imread('target.png');
source = rgb2gray(source);
target = rgb2gray(target);
sourcePoints=detectSURFFeatures(source,'MetricThreshold',100.0,'NumOctaves',1,'NumScaleLevels',6);
targetPoints=detectSURFFeatures(target,'MetricThreshold',100.0,'NumOctaves',1,'NumScaleLevels',6);
%figure; imshow(source);
%hold on;
%plot(sourcePoints.selectStrongest(10000));
[sourceFeatures, sourcePoints]=extractFeatures(source,sourcePoints,'SURFSize',64);
[targetFeatures,targetPoints]=extractFeatures(target,targetPoints,'SURFSize',64);
boxPairs = matchFeatures(sourceFeatures, targetFeatures);
matchedSourcePoints = sourcePoints(boxPairs(:, 1), :);
matchedTargetPoints = targetPoints(boxPairs(:, 2), :);
figure;
showMatchedFeatures(source, target, matchedSourcePoints, matchedTargetPoints, 'montage');
display(matchedSourcePoints);
display(matchedTargetPoints);
The problem is that from what i know you have functions that only display matched SURF Points, and i would need to plot on the target image only the points that didn't match with the points in the source image.
The resulting "matchedTargetPoints" and the "targetPoints" variables are arrays of SURFPoints objects, so the find function doesn't work, subtracting or making array operations on them don't work.
I also tried to loop through "targetPoints" and check for every one if the point exists, but the script takes forever, so this also doesn't work.
Does anyone have any idea how this might be accomplished?
Any response is appreciated.
Thank you.
You can get the (x,y) locations of the points stored in an M-by-2 matrix by using the Location property of the SURFPoints object. Then you can get the unmatched points using logical indexing:
targetPointsLoc = targetPoints.Location;
unmatchedIdx = true(size(targetPoitnsLoc, 1), 1);
unmatchedIdx(boxPairs(:, 2)) = false;
unmatchedTargetPoints = targetPointsLoc(unmatchedIdx, :);
Now you can use plot to display the unmatched points.
Out of curiosity, why do you care about the unmatched points?