Enhancing Radiological Diagnosis: A Collaborative Approach Integrating AI and Human Expertise for Visual Miss Correction

https://drive.google.com/drive/folders/1h9ZoITAITS_mvGjyZi8dHUpo8dMn_tHz?usp=sharing

1. Chexformer
2. Spatio-Temporal Abnormal Region Extractor (STARE )

Orginally Chexformer is trained on the Chexpert Dataset and we provide the pretrained chexformer model below. We also provide a sample of dataset for training and testing the Chexformer on the below link

1. Chexformer model Pretrained model

   https://drive.google.com/file/d/1SJeXGdqveZerVSfHEFRsxVo3TPY1FoId/view?usp=sharing

2. Chexformer Dataset [ Train & Val ]

   https://stanfordaimi.azurewebsites.net/datasets/8cbd9ed4-2eb9-4565-affc-111cf4f7ebe2

python main.py  --batch_size 16  --lr 0.00001 --optim 'adam' --layers 3  --dataroot data/

python main.py  --batch_size 16  --lr 0.00001 --optim 'adam' --layers 3  --dataroot data/ --inference --saved_model_name=''

STARE module is trained on the combination of REFLACX and Egd-cxr. We provide the detailed discription and download link for the pre-processed dataset on the Data readme file. We provide the pre-trained model for STARE below

1. STARE ( Pretrained model ):

2. Sample Training Data (Not full )

   • Extracted Video spatial features: Frame features extracted by clipvit(spatial encoder ) can be downloaded below for the STARE module [ Train + Some Test samples]

     https://drive.google.com/file/d/1rwNMLTfh0twaSlIqu9vY93OTFb1GT1kL/view?usp=drive_link

   • Ground Truth Summarized Reports: [Only Train]

     https://drive.google.com/file/d/1io2FGE2IC1LtLmFWLO3yIB9BAq5SNKzL/view?usp=sharing

   • Input Summarized Reports:[Only Train]

     https://drive.google.com/file/d/116pd5J2UZWykJqFZ4NLejxtZBkAD65ve/view?usp=sharing

python -m torch.distributed.launch --nproc_per_node 8 --use_env dvc.py --epochs=100 --lr=3e-4 --save_dir=vit --batch_size=2 --batch_size_val=2 --schedule="cosine_with_warmup"

To run the CoRaX on the Error dataset please use the Notebook uploaded above ## CoRaX-Errror_correction_final_file.ipynb ## . It uses the pretrained Chexformer and STARE which is provided on the below link. Please download from there.

https://drive.google.com/file/d/17fPfag9rBNmHMdFrwWIIfWUX6OKbjWZ9/view?usp=sharing

https://drive.google.com/file/d/1SJeXGdqveZerVSfHEFRsxVo3TPY1FoId/view?usp=sharing

https://drive.google.com/drive/folders/1h9ZoITAITS_mvGjyZi8dHUpo8dMn_tHz?usp=sharing

https://drive.google.com/file/d/1XK9AoiXHKegUTQPK8mZW1VGfRCjySgnR/view?usp=sharing