Clinically-Informed Preprocessing for ISLES'24 Stroke Segmentation

This is the docker files for the paper "Clinically-Informed Preprocessing Improves Stroke Segmentation in Low-Resource Settings".

Authors: Juampablo E. Heras Rivera*, Hitender Oswal*, Tianyi Ren*, Yutong Pan, William Henry, Caitlin M. Neher, Mehmet Kurt

* Co-first authors

Instructions

1. Clone this repository.

2. Download the model weights from the "model weights.txt" file (https://drive.google.com/drive/folders/1ZoTjTzbMT5EHo5KJZp6CL2U8qBLMZbXu?usp=sharing). Place the files inside the folder called "results" in the same directory as inference.py

3. Test the algorithm by running ./test_run.sh. This script should predict the example image, saving the result in test/output/.