How to mask a DICOM image?

Question

I would like to analyze only "Bone" regions extracted from Head CT.

For that, I read the DICOM files and masked regions where pixel values were less than 200 by filling in "0".

However, because "0" means "water" in the DICOM image, I don't know whether this is an appropriate way or not.

import pydicom
import numpy as np

dcm_img = pydicom.dcmread("0000200.dcm")
dcm_arr = dcm_img.pixel_array
masked_arr = np.where(dcm_arr < 200, 0, dcm_arr)

Answer 1

From your question, it is not quite clear to me how exactly you want to analyze the bone regions in your CT image, so it is hard to provide a tailored answer. Generally though, I would not set values to zero in the image, because – as you said – each value in a CT image is associated with specific tissue properties (also, very generally in image processing, it is usually not a good idea to conflate image and masking information).

Instead, I would probably work with a masked array, masking out all the values that lie below the bone threshold, like so:

from numpy.ma import masked_array
...
masked_arr = masked_array(data=dcm_arr, mask=dcm_arr < 200)

With this, you could then use the operations that a masked array provides, such as masked_arr.mean(), which calculates the mean of all voxels that have not been masked out (which is why we masked the values below the threshold).

Alternatively, but very similar, I would probably create a new (regular) Numpy array, containing a boolean mask that marks all the values that do lie above the bone threshold (e.g. is_bone = dcm_arr >= 200), which I would later use for filtering values in my analyses.

In any case, I would try to keep the mask values and the actual CT voxel values separate.