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Fully Convolutional Network Architecture for the Automation of MR Image Segmentation

load data

  • load_dicom
    • loads all the .dcm files in a filepath into a np.ndarray
  • load_nrrd
    • loads a single .nrrd file from filepath into a np.ndarray
    • optionally returns the header information

Network Architecture and Ideas:

  • Fully Convolutional Network
  • Mark regions that are somewhat uncertain
    • Use Seg3D2 or own simple verification application
    • Different mask for each tissue + different mask for uncertain tissues
    • Re-trainable with new data -> after manual verification

Issues:

  • Output format?
  • Prevent Catastrophic Forgetting
  • Keep lr python currentLearningRate = K.get_value(model.optimizer.lr)