how to center MRI images

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I work on MRIs. The problem is that the images are not always centered. In addition, there are often black bands around the patient's body.

I would like to be able to remove the black borders and center the patient's body like this: enter image description here enter image description here

I have already tried to determine the edges of the patient's body by reading the pixel table but I haven't come up with anything very conclusive.

In fact my solution works on only 50% of the images... I don't see any other way to do it...

Development environment: Python3.7 + OpenCV3.4

opencv image-processing python
2 Answers

I'm not sure this is the standard or most efficient way to do this, but it seems to work:

# Load image as grayscale (since it's b&w to start with)
im = cv2.imread('im.jpg', cv2.IMREAD_GRAYSCALE)

# Threshold it. I tried a few pixel values, and got something reasonable at min = 5
_,thresh = cv2.threshold(im,5,255,cv2.THRESH_BINARY)

# Find contours:
im2, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

# Put all contours together and reshape to (_,2).
# The first "column" will be your x values of your contours, and second will be y values
c = np.vstack(contours).reshape(-1,2)

# Extract the most left, most right, uppermost and lowermost point
xmin = np.min(c[:,0])
ymin = np.min(c[:,1])
xmax = np.max(c[:,0])
ymax = np.max(c[:,1])

# Use those as a guide of where to crop your image
crop = im[ymin:ymax, xmin:xmax]

cv2.imwrite('cropped.jpg', crop)

What you get in the end is this:

cropped_image

user_66711760

There are multiple ways to do this, and this is answer is pretty much computer vision tips and tricks.

If the mass is in the center, and the area outside is always going to be black, you can threshold the image and then find the edge pixels like you already are. I'd add 10 pixels to the border to adjust for variances in the threshold process.

Or if the body is always similarly sized, you can find the centroid of the blob (white area in the threshold image), and then crop a fixed area around it.

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