Comments (2)
ginobilinie
commented on August 12, 2024
Actually, this copy of code has been applied to PET/CT synthesis. Just check if it is single-modality input or multi-modality input.
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SurbhiKhushu
commented on August 12, 2024
My source is PET and target is generating CT data. It will be single modality input, I suppose:
Can you expalin what is matFA, matSeg, matMask in line 74:
def extractPatch4OneSubject(matFA, matSeg, matMask, fileID, d, step, rate):
Since I have preprocessed my DICOM slices and saved it as a volume data into a flat file .mf2 format.
I want to extract patches of size to 64 × 64 × 64 .
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Related Issues (20)
- MRI datasets synthetic CT datasets HOT 2
- Why loss is rising
- Error when importing gauss HOT 1
- gdl _loss is in TF vision HOT 1
- run “extract23Dpatches4SingleImg.py” HOT 2
- How to run the code on CPU for smaller dataset?
- RuntimeError Output size is too small HOT 9
- Updating how to run the pytorch code instruction HOT 1
- lambda parameter settings HOT 6
- Patch Exctraction Doubt HOT 3
- Final output resconstructed from patches to image HOT 5
- Generator_3D_patches HOT 1
- Implementation of ACM HOT 1
- The inputKey and outoutKey parameters
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- MRI data
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