/DigitalMammographyEnsembleValidation

External validation of the DREAM Digital Mammography Competition Ensemble Model

Primary LanguagePython

DigitalMammographyEnsembleValidation

External validation of the DREAM Digital Mammography Competition Ensemble Model

  1. Download Docker images of the Ensemble Models

    docker login docker.synapse.org docker pull docker.synapse.org/syn7887972/9646823/scoring docker pull docker.synapse.org/syn7887972/9648211/scoring docker pull docker.synapse.org/syn7887972/9648881/scoring docker pull docker.synapse.org/syn7887972/9648888/scoring docker pull docker.synapse.org/syn7887972/9648889/scoring docker pull docker.synapse.org/syn7887972/9648917/scoring docker pull docker.synapse.org/syn7887972/9650054/scoring docker pull docker.synapse.org/syn7887972/9650055/scoring docker pull docker.synapse.org/syn7887972/9650232/scoring docker pull docker.synapse.org/syn7887972/9650290/scoring docker pull docker.synapse.org/syn7887972/9650300/scoring

If Docker images cannot be downloaded, one needs to contact DREAM Challenge team for download permission.

  1. Prepare metadata and imaging files by running the Python program, sc2_data_prep.py. Output: ./images: DICOM image files ./metadata/exams_metadata.tsv ./metadata/images_crosswalk.tsv

    When facing a large number of exams, the software can divide exams into sub-collections. User can specify a max number of subjects to be in a collection through a command-line argument.

  2. Launch SC2 DREAM challenge ensemble models place both 'metadata' and 'images' in a same parent directory. In the parent directory, copy and run the following shell program.

    run_sc2_models.sh When running the models for sub-collections, copy 'run_sc2_models.sh' over and run it in each sub-collection.