Phoebe—A tool for Fast Visualisation of Time Series Volumetric Data

Mr Oliver Cairncross1

1Research Computing Centre, University of Queensland, Brisbane, Australia,



Modern high throughput microscopy instruments, such as lattice light-sheet microscopy (LLSM), generate large volumes of data necessitating the development of new systems to facilitate computation and analysis in a timely and efficient manner. Phoebe is such a system and it provides a means for researchers to visually survey these datasets quickly and efficiently. The purpose of this presentation is to discusses and demonstrate a 3D real time visualiser developed at the University of Queensland’s Research Computing Centre in collaboration with the Institute of Molecular Bioscience’s Stow Lab.

Extended Abstract

This presentation will detail several components that make up an integrated visualisation system for large scale time series volumetric data. Namely:

  • A pre-processing stage, converting LLSM data into manageable datasets for consumption downstream;
  • A computationally intensive, high performance, distributed processing engine deployed on clusters to produce meshes for visualisation;
  • A multiplatform lightweight visualiser allowing researchers to explore the data as well as drive the entire process from their desktops

The pre-processing stage serves as the entry point of the visualisation pipeline. It utilises various tools (such as ImageJ, ITK or custom software) to convert raw LLSM images into a format that can easily be used downstream. Note that various types of volume base imaging data could be converted for use by the visualiser. The system is not limited to LLSM data.

The visualiser and processing engine are tightly coupled to provide a flexible and responsive visualisation service. End users drive the process from a desktop application which directs the backend compute processes to vary depending on what timepoint and / or parameters the user chooses to asses. As soon as changes are made by the user the system provides immediate visual feedback by continually adjusting work queues and pushing out results to the desktop. These results are computed and pushed on an individual timepoint basis (as opposed to waiting for the entire time series to be computed) enabling researches to quickly move about in the dataset in a non-linear fashion.


Oliver Cairncross is a data visualisation specialist at the Research Computing Centre, University of Queensland. He has been working in the field of scientific computing for a decade starting with large database systems for storing electron microscope tomography data. Since then Oliver has been involved in various research fields with a focus on developing novel data visualisations techniques.

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