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This repository has been archived by the owner on Apr 4, 2023. It is now read-only.
I have a question to match different 3D medical dataset into same dataset size without losing or tilting medical information.
I am trying to match medical image using nib.Nifti1Image(image_resized, affine=None), but this seems changing medical data information.
The text was updated successfully, but these errors were encountered:
Our preprocessing stage also resizes all image crops to the same resolution. The spacing information will be changed, but the resulting deformation field can be transformed back.
The demo assumes the inputs being of DICOM series. The preprocessing stage first finds a rough bounding box of the liver area (using a threshold-based algorithm), crop the area accordingly and resize to 128^3, and then normalizes the intensity.
I have a question to match different 3D medical dataset into same dataset size without losing or tilting medical information.
I am trying to match medical image using nib.Nifti1Image(image_resized, affine=None), but this seems changing medical data information.
The text was updated successfully, but these errors were encountered: