RATCHET: RAdiological Text Captioning for Human Examined Thoraxes
RATCHET is a Medical Transformer for Chest X-ray Diagnosis and Reporting. Based on the architecture featured in Attention Is All You Need. This network is trained and validated on the MIMIC-CXR v2.0.0 dataset.
Run the code
streamlit run web_demo.py
imageio 2.8.0 matplotlib 3.2.1 numpy 1.18.4 pandas 1.0.3 scikit-image 0.17.2 streamlit 0.67.1 tensorflow-gpu 2.3.0 tokenizers 0.7.0 tqdm 4.46.0
Build the docker container:
docker build -t ratchet ./Dockerfile
Run the docker image on CXR images:
docker run --user $(id -u):$(id -g) \ -v /path/to/image_input_folder:/code/RATCHET/inp_folder \ -v /path/to/report_output_folder:/code/RATCHET/out_folder:rw \ -i -t ratchet python run_model.py
Each image in
inp_folder would have a corresponding
.txt report saved in
In comparison with the study of ___, there is little overall change. Again there is substantial enlargement of the cardiac silhouette with a dual-channel pacer device in place. No evidence of vascular congestion or acute focal pneumonia. Blunting of the costophrenic angles is again seen.