Dr Nishanthi Dasanayaka1, Dr Mark Endrei1, Dr Nicholas Condon2, Dr James Springfield2
1Research Computing Center, The University of Queensland, Brisbane, Australia, 2Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
Biography:
Nishanthi Dasanayaka is a Research Software Engineer at the Research Computing Centre, The University of Queensland, with nearly three years of experience in eResearch portal development. She holds a PhD in Computer Science from Queensland University of Technology, Brisbane. With a background in system architecture design and algorithm development, her work focuses on integrating advanced web technologies and computational methods to develop scalable eResearch platforms that support UQ researchers.
Mark Endrei is a senior principal research software engineer at the Research Computing Centre, The University of Queensland, Australia. He also has more than 20 years of experience in IT industry, working with large corporations both nationally and internationally. He has a PhD from The University of Queensland and a Bachelor of Engineering Degree (H1) in Computer Systems Engineering from RMIT University.
Abstract:
Modern light-sheet microscopy techniques produce terabytes of high-resolution, time-lapse imaging data per experiment, posing major challenges in data management and analysis. To address this, we developed the Image Processing Portal (IPP)- a web-based platform enabling researchers to process microscopy datasets using organizational High-Performance Computing (HPC) resources without requiring command-line skills.
Developed in partnership with the Research Computing Centre’s Metropolitan Data Caching Infrastructure (MeDICI) at the University of Queensland (UQ), IPP simplifies GPU-accelerated image analysis tasks such as deconvolution, file conversion, batch processing, deskewing, and image transformations such as Z-projection. Users can interact with HPC file systems, run macros from shared repositories, perform deconvolution through an integrated metadata extraction pipeline, and soon, automatic 3D stitching of Teravoxel-sized tiled microscopy images through tools such as TeraStitcher -all via an intuitive web interface.
Recent enhancements add significant new functional and infrastructure improvements. Deployment of the IPP portal was modernized from Docker Compose to Kubernetes, providing improved scalability, reliability, and efficiency. We also review migrating the IPP app from the now retired Wiener supercomputer to UQ’s next-generation Bunya supercomputer, enabling faster processing, improved GPU access, and integration with interactive visual computing via onDemand.
These developments transform IPP into a robust, scalable solution for large-scale image analysis, accessible to non-specialist users and adaptable to evolving research needs. IPP now offers researchers a user-friendly, HPC-powered image processing, lowering HPC and cloud computing technical barriers.