Australian Imaging Service
The Australian Imaging Service (AIS) is a national project led by Dr Ryan Sullivan at the University of Sydney, with key operational and development support provided by Sydney Imaging staff such as Dr Thomas Close, who leads the AIS integrated analysis pipelines team. AIS was established in collaboration with the Australian Research Data Commons (ARDC), the National Imaging Facility (NIF), and partner universities and research organisations. AIS aims to standardise and integrate the XNAT platform for imaging research in a distributed federation.
The federated access system of AIS caters to the requirements of Australian researchers and imaging experts, especially those involved in clinical, preclinical, veterinary, and archaeological imaging, addressing significant data challenges. AIS streamlines user authentication, integrates instruments, defines data ontologies, and provides sophisticated software tools, all aimed at bolstering research reproducibility.
AIS operates as a federation with a central set of software repositories. Partner institutions maintain their nodes, integrating local governance and infrastructure. The platform follows a hub-and-spoke model, connecting nodes with imaging devices, and facilitating multi-site studies.
- The University of Sydney
- National Imaging Facility
- Macquarie University
- Queensland Cyber Infrastructure Foundation
- Queensland University of Technology
- The University of Queensland
- University of New South Wales Sydney
- Neuroscience Research Australia
- The University of Western Australia
- South Australian Health and Medical Research Institute
AIS encompasses four integrated capability areas to optimise functionality.
- Prioritising secure, audited data management, access, and de-identification, utilising the XNAT framework as a foundation.
- Employing non-interactive pipelines specifically designed for repository-centric analysis through Arcana.
- Enabling interactive analysis through the seamless integration of Jupyter and Neurodesk, providing secure virtual desktops.
- Advancing its machine learning capabilities, starting with MONAI Label—a dedicated tool for AI-assisted image annotation and segmentation.
- Integration with imaging facilities and clinical sites
- Secure, audited data management, access, and de-identification
- Browser accessible viewing, annotation, and analysis
- One-click reproducible pipeline library, curated collection, and custom developed
University of Sydney community
- Leverage AIS to enhance imaging research capabilities
- Collaborate with partner institutions and contribute to national and international projects
Researchers and imaging specialists
- Access AIS through one of the federated nodes
- Utilise standardised authentication, instrument integration, and data ontologies
Medical research organisations
- Access simplified deployment of XNAT across infrastructures.
- Federated access to data and analysis pipelines through the Australian Access Federation (AAF).
For access enquiries, please contact ais.admin@sydney.edu.au
AIS has supported hundreds of users across more than 200 projects. Examples include:
- the global MSBase Imaging Repository (MSBIR) for secure sharing and analysis of de-identified clinical images of multiple sclerosis (MS), enabled by the AIS’ cloud-native design
- the ACRF Australian Centre of Excellence in Melanoma and Diagnosis (ACEMID)
- multiple Medical Research Future Fund (MRFF) projects.
The AIS has also worked with other ARDC-supported projects, including the: