How should I approach the problem of removing negative pixels from MRI slices (or any image)?
Also, it would really help if someone can briefly explain why they occur.
I have read many online references especially those on MATLAB forum, but they seem to have diverse reasons as to why they occur.
Sorry, I don't have a code to post, since I am figuring out my approach yet.
An MRI slice is presumably for us here nothing but an image, which is also nothing but a matrix. Since a matrix representing an image have only positive values, 'a negative pixel' also, presumably, mean the pixels having a value lower than a certain threshold. Let's have such a scenario:
load clown loads a matrix X to your workspace representing a clown image, to see it first do imagesc(X);colormap(gray);. If you want to cut out some values lower than a threshold, you can do:
threshold=10;
newValue=0;
X(find(X>threshold))=newValue;
imagesc(X)
colormap(gray)
Assume for example the following image matrix:
>> Img = [-2, -1, 0, 1, 2];
You could set all negative elements to zero:
>> ImgZeros = Img;
>> ImgZeros(Img<0) = 0
ImgZeros =
0 0 0 1 2
Or any other value useful to you, e.g. NaN:
>> ImgNans = Img;
>> ImgNans(Img<0) = nan
ImgNans =
NaN NaN 0 1 2
You could 'shift' all the values up such that the lowest negative value becomes zero:
>> ImgZeroFloor = Img - min(Img(:))
ImgZeroFloor =
0 1 2 3 4
You could convert the whole thing to a grayscale image in the range (0,1):
>> ImgGray = mat2gray(Img)
ImgGray =
0 0.2500 0.5000 0.7500 1.0000
etc.
As to why you're getting negative values, who knows. It's problem specific. (If I had to guess for MRI I would say it's due to numerical inaccuracy during the conversion process from an MRI signal to pixel intensities.)
Another way to limit your values is to use a sigmoid function
https://en.wikipedia.org/wiki/Sigmoid_function
It can be scaled so that all answers range from 0 to 255 And it can be used to limit the spikes in raw data balance. Its often used in neural networks.
