feature extraction for MRI image

hi. I want to extract features for analyzing an image. I have extracted 8 basic features such as energy, homogeneity, contrast, skewness, correlation, variance etc. What other features can i use for image classification? My image is a cancer MRI. Thanks in advance. Have a nice day :)

Answer 1

[Image Analyst]

Too many to list. See VisionBib for lots of algorithms to measure all kinds of things.

Answer 2

[Rafee Muhammad]

%% Image Read
[filename, pathname] = uigetfile({'*.jpg'; '*.bmp'; '*.tif'; '*.gif'; '*.png'; '*.jpeg'}, 'Load Image File');
brainImg = imread([pathname filename]);
subplot(231);imshow(brainImg);title('Input image','FontSize',20);

%% preprocessing
[m n c] = size(brainImg);
if c == 3
    brainImg  = rgb2gray(brainImg);
end
[ brainImg ] = Preprocess( brainImg );
subplot(232);imshow(brainImg);title('preprocessed image','FontSize',20);
%% Convert To Binary
img2 = im2bw(brainImg);
%% Feature Extraction
signal1 = img2(:,:);
    [cA1,cH1,cV1,cD1] = dwt2(signal1,'db4');
    [cA2,cH2,cV2,cD2] = dwt2(cA1,'db4');
    [cA3,cH3,cV3,cD3] = dwt2(cA2,'db4');

    DWT_feat = [cA3,cH3,cV3,cD3];
    G = pca(DWT_feat);
    whos DWT_feat
    whos G
    g = graycomatrix(G);
    stats = graycoprops(g,'Contrast Correlation Energy Homogeneity');
    Contrast = stats.Contrast;
    Correlation = stats.Correlation;
    Energy = stats.Energy;
    Homogeneity = stats.Homogeneity;
    Mean = mean2(G);
    Standard_Deviation = std2(G);
    Entropy = entropy(G);
    RMS = mean2(rms(G));
    %Skewness = skewness(img)
    Variance = mean2(var(double(G)));
    a = sum(double(G(:)));
    Smoothness = 1-(1/(1+a));
    Kurtosis = kurtosis(double(G(:)));
    Skewness = skewness(double(G(:)));

[Emma Stone]

Hello Sir,

in your code we don't have information about preprocess function ,it gives error in below line, would you suggest me whats the issue!

[ brainImg ] = Preprocess( brainImg );

thanks

[Priyanka Matta]

Hello Rafee,

I tried your code for extracting features in a IVUS image.

It worked very well.

thanks

Answer 3

[farheen asdf]

I have finally trained my neural network and the results are good (87% accurate). That being said i'm still a little confused as to how it can be used practically. For example, in my case it takes the network several tries to get to 87% accuracy. Sometimes its accuracy is as bad as 26%. How can i make sure that my network remembers what it has learned when it gets to 87% accuracy? Second, i was wondering if i could use this network to find the class of an unknown image which i select at runtime. I've used indexing method to separate the training, validation and test data so that the network tests only the images i want it to. Thanks in advance. Have a nice day :)

[Image Analyst]

I don't use Neural Networks. I've added the Product Neural Network Toolbox above, so maybe Greg Heath will see it and answer you.

[farheen asdf]

Thank you Image Analyst

Answer 4

[Foading Leonce]

Hello @Rafee Muhammad. Thanks for your contribution.

But in your code we don't have information about preprocess function in this line:

[ brainImg ] = Preprocess( brainImg );

Please supply that function. Thanks. 🙂

[Fatima]

Me too

[Image Analyst]

@Foading Leonce and @Fatima you might be able to get away without even using that line of code. We don't know what he did. Maybe it was just something you don't need to do, like cropping his image. Try it without that line of code (comment it out) and see how it works.

Answer 5

[Fatima]

Me too

[Image Analyst]

https://www.mathworks.com/matlabcentral/answers/224708-feature-extraction-for-mri-image#comment_2502302