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)