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a b/combinedDeepLearningActiveContour/functions/normalizeData.m
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function patches = normalizeData(patches)
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% Squash data to [0.1, 0.9] since we use sigmoid as the activation
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% function in the output layer
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% Remove DC (mean of images). 
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patches = bsxfun(@minus, patches, mean(patches));
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% Truncate to +/-3 standard deviations and scale to -1 to 1
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pstd = 3 * std(patches(:));
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patches = max(min(patches, pstd), -pstd) / pstd;
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% Rescale from [-1,1] to [0.1,0.9]
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patches = (patches + 1) * 0.4 + 0.1;
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end