REAP

This is the repository of Improving Radiology Report Generation with Explicit Abnormality Prediction.

Requirements

• torch==1.7.1
• torchvision==0.8.2
• opencv-python==4.4.0.42

Download REAP

We will release weight files later.

Datasets

We use two datasets (IU X-Ray and MIMIC-CXR) in our paper.

For IU X-Ray, you can download the dataset from here and then put the files in data/iu_xray.

For MIMIC-CXR, you can download the dataset from here and then put the files in data/mimic_cxr.

NOTE: The IU X-Ray dataset is of small size, and thus the variance of the results is large. There have been some works using MIMIC-CXR only and treating the whole IU X-Ray dataset as an extra test set.

Usage

see shells.sh to get the command for train and test