Organ-aware 3D lesion segmentation dataset and pipeline for abdominal CT analysis (ACM Multimedia 2025 candidate)
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To_Dicom.py 414B

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  1. import pyplastimatch as pypla
  2. from pyplastimatch.utils.install import install_precompiled_binaries
  3. install_precompiled_binaries("")
  4. # convert one of the NIFTI images to DICOM: name: <patient1>, output folder: <dicom_output>
  5. convert_args_ct = {
  6. "input": "datasets/004428_01_02_182-242.nii.gz",
  7. "patient-id": "patient1",
  8. "output-dicom": "dicom_output",
  9. }
  10. pypla.convert(verbose=True, **convert_args_ct)