feature extraction for MRI image

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farheen asdf
farheen asdf el 21 de Jun. de 2015
Comentada: Image Analyst el 6 de Dic. de 2022
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 :)

Respuesta aceptada

Image Analyst
Image Analyst el 21 de Jun. de 2015
Too many to list. See VisionBib for lots of algorithms to measure all kinds of things.

M谩s respuestas (4)

Rafee Muhammad
Rafee Muhammad el 11 de Feb. de 2019
%% 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(:)));
  2 comentarios
Emma Stone
Emma Stone el 10 de Nov. de 2020
Editada: Emma Stone el 10 de Nov. de 2020
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
Priyanka Matta el 20 de Mayo de 2021
Hello Rafee,
I tried your code for extracting features in a IVUS image.
It worked very well.
thanks

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farheen asdf
farheen asdf el 2 de Jul. de 2015
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 :)
  2 comentarios
Image Analyst
Image Analyst el 2 de Jul. de 2015
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
farheen asdf el 3 de Jul. de 2015
Thank you Image Analyst

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Foading Leonce
Foading Leonce el 10 de Mzo. de 2019
Editada: Image Analyst el 5 de Dic. de 2022
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. 馃檪
  2 comentarios
Fatima
Fatima el 5 de Dic. de 2022
Me too
Image Analyst
Image Analyst el 5 de Dic. de 2022
@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.

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Fatima
Fatima el 5 de Dic. de 2022
Me too

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