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How to extract the main square, image window of the ultrasound image?

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I need some help.
How do I extract/crop the main square of the ultrasound image. The image window that shows the valuable information and discard all the rest black and annotations.
Looking forward to your valuable help

Risposta accettata

Constantino Carlos Reyes-Aldasoro
Ok, the issue here is the colour maps and the conversion of uint8 to double. If you convert to double the colours are always between 0 and 1, so you would need to divide by the maximum value (in this case 255)
imagesc(double(A6__14_9N_).*(repmat(1-(background),[1 1 3]))/255)
OR you can convert to uint8 the background:
imagesc(A6__14_9N_.*(repmat(1-uint8(background),[1 1 3])))
Both should work.
  2 Commenti
Stelios Fanourakis
Stelios Fanourakis il 27 Set 2019
Yes they work. Thank you very much. And how do I remove the black background and keep only the gray square?
Constantino Carlos Reyes-Aldasoro
Ok, that is a bit different. You basically need to find the limits of rows and columns. Find the complement of the background
and sum over the columns and rows
sum( ,1)
sum( ,2)
That would generate 1D vectors where the foreground exist. The use the function "find" and select the first non-zero element (that will give you the first row/column) and the last (final row/column) and with that you can crop into a new matrix.

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Più risposte (2)

Constantino Carlos Reyes-Aldasoro
Hard to answer without knowing your data. Post a sample and we can try.

Constantino Carlos Reyes-Aldasoro
*IF* all the images look like this, it is rather easy, EXCEPT for the fact that the bottom edge of the ultrasound is not very well defined.
The key is to find the background to determine the foreground, The background is black, so take only one channel (the image is RGB), compare against zero and that would give the background but with the annotations and bits you want to remove, so close the image with imclose with a structural element sufficiently large to cover those elements:
background =(imclose(A6__14_9N_(:,:,1)==0,ones(25)));
Then, you only need to take the complement and recover the ultrasound part
imagesc(A6__14_9N_.*(repmat(1-background,[1 1 3])))
If you compare with the original, it seems that the job is done.
  5 Commenti
Stelios Fanourakis
Stelios Fanourakis il 27 Set 2019
I think that when I convert it to double it gets black and white.

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