Tag Archives: Antony Orth

Dictionary-enhanced imaging cytometry

22 February 2017:

A new paper by CNBP researcher Tony Orth (lead author pictured) describes how to use large image sets to perform cell classification and imaging performance. The work combines years of hardware development on a high throughput microlens microscope together with large scale image processing.

The authors on the paper found that they could get a computer to accurately identify white blood cells types purely from a reference set of images (or dictionary), without resorting to time-consuming manual classification by trained staff.

Moreover, the authors demonstrated that because white blood cells come in a limited number of shapes and sizes, even a very poor quality noisy image of a white blood cell can be effectively enhanced by looking for similar images in the dictionary set.

This has potential applications for low-light level imaging. Working with a small amount of light is detrimental in terms of image quality but gentle on cells. The author’s dictionary-based method provides a way to partially recover image quality for dose-limited imaging.

The paper is accessible online.

Dictionary-enhanced imaging cytometry. Antony Orth, Diane Schaak and Ethan Schonbrun. Scientific Reports 7, Article number: 43148 (2017).

Science ‘Experience Day’ at RMIT

18 January 2017:

Researchers at CNBP’s RMIT University node were busy doing light-based demonstrations on Wednesday Jan 18th, as part of the ‘RMIT University Experience Day’ program, whereby students from years 10, 11 and 12 get to engage in hands-on workshops and explore life on campus while experiencing the differing aspects of University discipline areas.

As part of the ‘experience’ activity, over seventy high school students (predominantly in Year 10) visited the CNBP researchers in their physics laboratories. While there, students were given an overview of biophotonic science as well as laboratory research, and shown the exciting things that can be done with light including 3D scanning, fluorescence microscopy and more.

Below – CNBP researcher Philipp Reineck talks and demonstrates photonics to students.




Best paper award at SPIE Photonics West

Antony_Orth_web18 March 2016:

Congratulations to CNBP Research Fellow Antony Orth who has won a Hitachi Hi-Tech award for a paper presented at the recent SPIE Photonics West BIOS 2016 conference (High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management).

There were six awards distributed to authors who presented at the conference, with Antony’s talk titled “Gigapixel microscopy with microlens arrays.”

Awarded participants had to be both the primary author and presenter of an accepted abstract to be eligible. Qualifying papers and presentations were then evaluated by the awards committee.

Well done on your award Antony!

Orth talks at SPIE Micro+Nano conference

Antony_Orth_web8 December 2015:

‘Gigapixel hyperspectral microscopy for high content analysis’ was the talk undertaken by CNBP Research Fellow Antony Orth, at the SPIE Micro+Nano Conference in Sydney, December, 2015.

The talk was based on the following research paper:

Paper title: Gigapixel hyperspectral microscopy for high content analysis.

Paper authors: Antony Orth, RMIT Univ. (Australia), The Rowland Institute (United States); Monica J. Tomaszewski, Richik N. Ghosh, Thermo Fisher Scientific Inc. (United States); Ethan F. Schonbrun, The Rowland Institute at Harvard (United States)

A key part of the drug discovery process relies on image-based assays to assess the efficacy of potential medical compounds. These assays can involve imaging up to millions of cells in many different colors – a time consuming task for today’s automated microscopes. We have developed a microlens-based microscope capable of acquiring large images faster and with more colors than current systems. We discuss system design, present gigapixel microscope images with up to 13 color channels, and demonstrate proof of concept spectral unmixing for a cell proliferation assay.