SABER (Scalable Analytics for Brain Exploration Research) is a library of containerized tools and a workflow deployment system for enabling processing of large neuroimaging datasets. Current workflows include processing of X-ray Microtomorography data to produce cell density estimates as well as processing Electron Microscopy images to segment neuron bodies. This project builds on Apache Airflow (http://airflow.apache.org) to orchestrate workflow deployment. This project interfaces with Datajoint (https://datajoint.io) and bossDB (https://github.com/jhuapl-boss/boss) to enable data storage and reproducible workflows.
SABER requires docker and docker-compose. Please use the latest versions. To run our example workflows, you will need an AWS account to enable cloud storage through the AWS S3 service (https://aws.amazon.com/account/). To access data for our example workflows you will need an account at https://api.bossdb.org
Simply clone this repository and run
docker-compose up -d inside it!
Please see our wiki for more information!
Please see our wiki for more information about public access to data for testing Electron Microscopy and X-ray Microtomography workflows.
Use or redistribution of the SABER system in source and/or binary forms, with or without modification, are permitted provided that the following conditions are met:
- Redistributions of source code or binary forms must adhere to the terms and conditions of any applicable software licenses.
- End-user documentation or notices, whether included as part of a redistribution or disseminated as part of a legal or scientific disclosure (e.g. publication) or advertisement, must include the following acknowledgement: The SABER software system was designed and developed by the Johns Hopkins University Applied Physics Laboratory (JHU/APL).
- The names "SABER", "JHU/APL", "Johns Hopkins University", "Applied Physics Laboratory" must not be used to endorse or promote products derived from this software without prior written permission. For written permission, please contact BossAdmin@jhuapl.edu.
- This source code and library is distributed in the hope that it will be useful, but is provided without any warranty of any kind.