Comments (6)
@jcreinhold That really makes sense. Thanks a lot :)
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Hi, I don't have any issue, but just had a question regarding z-score normalization. I am new to working with medical images and so I don't understand why do you do the z-score with a mask and not directly take the image, take mean and std and calculate. Could you please explain it to me?
from intensity-normalization.
Hi @vkyprmr—for future reference—if you have a feature request or question about unclear documentation, you should open up a new issue. But to answer your question, you can have z-score normalize use the entire image; if you use the zscore-normalize
script, then you can pass in none
for the option --brain-mask
. The script states this option in the argument description if you run zscore-normalize --help
in your terminal after you've installed this package.
Hope this helped.
from intensity-normalization.
I am sorry. I knew the programming side: specifying none
if needed. I was wandering more about the clinical side and what difference does it make. But, I am sorry if it was a dumb question. Good luck for the future.
from intensity-normalization.
@vkprmr I see. That's not a dumb question. I don't suspect that any of these normalization methods would be used for clinical work. These methods are mostly used as preprocessing for image processing/machine learning methods. With respect to z-score normalization with the brain mask, the normalization is usually more consistent across a image data set if you use the brain intensities to z-score normalize vs. the whole image.
Generally these normalization methods are used to put the tissue intensities into alignment across a dataset. z-score normalization works by subtracting the mean and dividing by the standard deviation (std) on every voxel—where the mean and std are computed either from the intensities in the brain mask or across the whole image. If the mean and std are computed from the whole image, the mean will be very close to zero (because the vast majority of voxels in a 3D volume are background) and the std will also not be as meaningful for the same reason.
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Completed with ede16c3
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Related Issues (20)
- Nyul normalize not working with custom output range HOT 11
- Confusing import errors for some CLI tools when ANTsPy isn't installed HOT 5
- Support printing version information HOT 1
- Add/check Python v3.10 support HOT 3
- Add a citation file
- Improve contributing information
- Add numpy mypy plugin HOT 1
- Improve unit tests HOT 1
- Verify correctness of update to use pymedio HOT 1
- Fix mypy issues in update to use pymedio HOT 2
- Add note about scanner gain in MR pulse sequence equations
- Add pre-commit hooks HOT 1
- Add option to specify output file type
- What is the "MD" modality? And other questions. HOT 14
- Out-of-memory error in Nyul for large amounts of data HOT 4
- `intensity-normalization` not working in Google Colab HOT 1
- "TypeError: Axis must be specified when shapes of a and weights differ." in the LSQ method
- problems when importing the API HOT 1
- request for tutorial of Z score HOT 9
- Update docs in the style of Diátaxis
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