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And MONAI is PyTorch-based, PyTorch use the |
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which version of MONAI is this related to? asking because recently there are some API enhancements in this area in both monai and itk-python |
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The lastest |
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When using the
LoadImage
transform, bothNibabelReader
andITKReader
load nifti file asWHD
data order, even ITKReader does a transpose for it, Although this dimension order is the same with some meta info in dicom, like spacing. But not for the best performance. Now, I use the MONAI trained model with ITK libraries in C++, it's very inconvenient. If using ITK functions, the data dimension order must beDHW
, but when using model to inference, I have to tranpose the image buffer(data) toWHD
, after inference, then tranpose the outputs back toDHW
and write to the ITK image buffer. Specifically if using slide window inference,the additional two tranpose and
WHD
order inference affect performance a lot. Is there some good methods to deal with this situation. Or can I train models withDHW
data order with MONAI?Beta Was this translation helpful? Give feedback.
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