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The official code of OCT2Former for Retinal OCT-Angiography vessel segmentation

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Python 3.9

OCT2Former

The official code of OCT2Former: A retinal OCT-angiography vessel segmentation transformer

Prerequisites

  • python3
  • numpy
  • pillow
  • opencv-python
  • scikit-learn
  • tensorboardX
  • visdom
  • pytorch
  • torchvision
  • pandas

FOR OCTA-SS dataset

python train.py --dataset='OCTA-SS'
--num_epochs=100
--dataset_file_list='utils/OCTA-SS.csv'
--data_root=$OCTA-SS-DATA-PATH
--target_root=$OCTA-SS-LABEL-PATH
--run_dir='OCTA-SS'
--in_channel=1
--batch_size=2
--lr=5e-4
--spec_interpolation
--img_aug

OR

sh trainSS.sh

FOR ROSE1 dataset

python train.py --dataset='ROSE'
--num_epochs=100
--dataset_file_list='utils/ROSE-1.csv'
--data_root=$ROSE-1-SS-DATA-PATH
--target_root=$ROSE-1-THICK-LABEL-PATH
--run_dir='ROSE-1'
--in_channel=1
--batch_size=2
--lr=5e-4
--img_aug

OR

sh trainROSE.sh

FOR OCTA-3M dataset

python train.py
--dataset='OCTA-3M'
--num_epochs=100
--dataset_file_list='utils/OCTA_3M.csv'
--data_root=$OCTA-3M-OCTA-DATA-PATH
--data_root_aux=$OCTA-3M-OCT-DATA-PATH
--target_root=$OCTA-3M-LABEL-PATH
--run_dir='3M'
--in_channel=2
--batch_size=2
--lr=5e-4
--img_aug \

OR

sh train3M.sh

FOR OCTA-6M dataset

python train.py
--dataset='OCTA-6M'
--num_epochs=100
--dataset_file_list='utils/OCTA_6M.csv'
--data_root=$OCTA-6M-OCTA-DATA-PATH
--data_root_aux=$OCTA-6M-OCT-DATA-PATH
--target_root=$OCTA-6M-LABEL-PATH
--run_dir='6M'
--in_channel=2
--batch_size=2
--lr=5e-4
--img_aug
--cuda_id=6

OR

sh train6M.sh

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