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Feature Autoencoder in ADNI

  1. Convert DICOM Files:

    • Run convert.sh to convert DICOM files to NIfTI format and apply skull stripping.
    • You can revise the INPUT and OUTPUT PATH in the convert.sh
  2. Set Up the Environment and Train the Model:

    • Create the conda environment and activate it:
      conda env create -f environment.yml
      conda activate anomaly_detection
    • Execute main.py to train the feature autoencoder on the processed data.
  3. Visualization:

    • To visualize the results, run Inference.py.

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