Training a neural netnork

I have two files one imageReader that reads ans get the co-occurence matrix all images in the dataset and the neuralnet which does the training at the testing. It seems like the imageReader is only returning the co-occurence matrix of one image. I would like to use the co-ccurence matrix of the images to train. I would also like to label the images (as either cancerous or non cancerous).

ImageReader file

function dataset = imageReader(Folder,imgType)

Imgs = dir([Folder '/' imgType]); NumImgs = size(Imgs,1); image = double(imread([Folder '/' Imgs(1).name])); dataset = zeros([NumImgs size(image)]);

for i=1:NumImgs, image = double(imread([Folder '/' Imgs(i).name]));

    [rows columns numberOfColorChannels] = size(Imgs);
    %%Check if the im loaded is a grayscale image

    if numberOfColorChannels > 1
        %%Coverting to grayscale & get the co-occurrence matrix
        F = graycomatrix(rgb2gray(imresize(image,[50 50])));
        dataset = F;
    else
        F= graycomatrix(imresize(image,[50 50])); %get co-occurrence matrix
        dataset = F;
    end

end

end

neuralNet file

function neuralNet()

net = feedforwardnet(10);

%Loop to get the features for all images x = imageReader('TrainingSet','*.png');

for j=1:20

end

% Create a Self-Organizing Map som = selforgmap([10 10]); som = train(som,x); t = som(x); %Extract class data %t should 0 or 1

%t'=[0,0,0,0,0,1,1,1,1,1]

% Train the Network net = train(net,x,t); msgbox(sprintf('Training Successful'),'Success','success');

% Test the Network outputs = net(x); % now test it with a new x errors = gsubtract(t,outputs); performance = perform(net,t,outputs)

% View the Network view(net)

end

Any one that can help me with the neural Network please. Thank you.