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pytorch-carcino-net

Pytorch implementation of Carcino-Net.

  • Use SICAPV2 prostate data for segmentation of negative (non-cancerous background), low grade (Gleason grade group 3), and high grade (Gleason grade group 4 and 5).

Usage:

python -m carcino_net.scripts.train_carcino --help for detail arguments of training scripts.

python -m carcino_net.scripts.validate_carcino --help for detail arguments of validation and to export showcase output masks.

To DO:

  • documentation

Disclaimer

  • Multi-class focal loss are directly derived from Adeel Hassan's implementation. Alternatively you may use the weighted cross entropy in pytorch combining the (1 - softmax score) as the focal term.