Derek Merck [email protected]
Brown University and Rhode Island Hospital
Winter 2018

Source: https://www.github.com/derekmerck/DIANA
Documentation: https://diana.readthedocs.io

Hospital picture archive and communications systems (PACS) are not well suited for "big data" analysis. It is difficult to identify and extract datasets in bulk, and moreover, high resolution data is often not even stored in the clinical systems.

DIANA is a DICOM imaging informatics platform that can be attached to the clinical systems with a very small footprint, and then tuned to support a range of tasks from high-resolution image archival to cohort discovery to radiation dose monitoring.

It is similar to XNAT in providing DICOM services, image data indexing, REST endpoints for scripting, and user access control. It is dissimilar in that it is not a monolithic codebase, but an amalgamation of free and free and open source (FOSS) systems.

• Python 2.7
• Many Python packages

$ git clone https://www.github.com/derekmerck/DIANA
$ pip install -r DIANA/requirements.txt

Ansible scripts for flexible, reproducible DICOM service configurations.

• DICOM image archives and routing (Orthanc)
• Data indexing and forwarding (Splunk)

Python scripts for data monitoring and transfer jobs.

• Update data indices with DICOM tag information
• Monitor available studies in PACS
• Build secondary image registries
• Identify image populations
• Automatic deidentification

A simple, dynanmically configured DIANA front-end html interface for accessing available imaging trial resources.

Reference implementation at http://www.central-imaging.com/

Splunk apps and dashboards for informatics and data review

• DIANA-status: DIANA services introspection
• RadRx: DICOM structured dose record monitoring
• RadFlow: hl7 feed analysis and radiologist workload balancing
• RadClf: Radiology report NLP classification

DICOM element ("dixel") wrapper classes for for Orthanc, Montage, Splunk, and files on disk.

Flexible, reproducible anonymization and hashing schemes and canonical ID server.

(Planned) Extensions supporting high-throughput microscopy data and image analytics and archive

• Monitoring for microscopy use logs
• Post-processing including ROI cropping and 3D CLAHE

MIT