Hi,
I am running the segmentation pipeline on my own glioma MRI dataset using the code in BRATS23/test.py. I noticed that the normalization parameters (a_min=-175.0, a_max=250.0, etc.) are typical for CT preprocessing. However, BRATS and my data are both MRI, and MRI images do not have standardized intensity ranges like CT.
I am observing poor segmentation performance on my glioma MRI data. I suspect this might be related to the normalization method, since z-score normalization (zero mean, unit variance) is usually recommended for MRI images.
Could you please confirm whether using these CT-specific normalization parameters is intentional for BRATS, or would it be more appropriate to use z-score normalization for MRI images in this case?
Thank you so much in advance.
Best
Xuewei
Hi,
I am running the segmentation pipeline on my own glioma MRI dataset using the code in BRATS23/test.py. I noticed that the normalization parameters (a_min=-175.0, a_max=250.0, etc.) are typical for CT preprocessing. However, BRATS and my data are both MRI, and MRI images do not have standardized intensity ranges like CT.
I am observing poor segmentation performance on my glioma MRI data. I suspect this might be related to the normalization method, since z-score normalization (zero mean, unit variance) is usually recommended for MRI images.
Could you please confirm whether using these CT-specific normalization parameters is intentional for BRATS, or would it be more appropriate to use z-score normalization for MRI images in this case?
Thank you so much in advance.
Best
Xuewei