email: ccha4217 |at| uni.sydney.edu.au
My research involves the use of Diffusion MRI to assist in the identification and characterization of prostate cancer. I am currently working on Monte Carlo simulations of diffusion in virtual cellular environments to mimic the prostate cellular environment. Am also interested in modelling analysis and regression methods for Diffusion MRI signal data. I use MATLAB for most image analysis, MevisLab to import and crop MRI DICOM data, and Python for both scientific and general purpose applications. I also program in C/C++/C# whenever needed and can get by using Java.
My main research project involves the analysis of whole organs and tissue samples from prostates extracted from surgery via prostatectomy due to prostate cancer diagnosis. We image the whole organ in a 9.4 T small animal scanner before and after fixation (see this paper) to get the high resolution organ images as seen below.
We also analyze high resolution MR images on a 16.4 T spectrometer on prostate core samples taken from pathology after dissection. These images have even higher resolution (~ 40 micron voxel size) to allow for diffusion analysis at the cellular level.
Masters of Science
In 2012, I completed a Masters of Science with the Astrophotonics group in the Sydney Institute for Astronomy, which is part of the School of Physics at the University of Sydney. The bulk of my work consisted of the design of path-length matched optical waveguides, which were fabricated on a single glass chip using a high-powered laser to form an optical interferometer. This interferometer was tested on the Anglo-Australian Telescope (AAT) and successful interferometric fringe measurements of a few stars were made. We published a paper based on our results here (or on arxiv here).
My Masters thesis is available online via the University of Sydney’s eScholarship Repository here, however, I did publish a paper on the bulk of my thesis work here. My waveguide design code for this paper (and my thesis) was written in Python and contains all of the functions I wrote to path length match the optical waveguides, as well as verify their spatial separation, calculate expected power loss, provide machine coordinates to the fabrication system, and display the waveguides in 3D using mayavi2, among others. You can download this code freely below, and all functions are contained in one file, which is both a strength and weakness, as is my penchant for long, explicit variable names. It could use a lot of work and a simple minimization algorithm would speed the length search portion considerably, but at that time, I didn’t have much experience with that sort of thing. If any of this Python code helps your work out, feel free to reference my paper.
OpticalWaveguideCreation (note, due to WordPress.com restrictions on source code uploading, I changed the extension of this .py file to and .odt file. Right click and save it and then change the extension back to .py)
Reference: N. Charles, N. Jovanovic, S. Gross, P. Stewart, B. Norris, J. O’Byrne, J. Lawrence, M. Withford, and P. Tuthill, “Design of optically path-length-matched, three-dimensional photonic circuits comprising uniquely routed waveguides,” Appl. Opt. 51, 6489-6497 (2012). http://dx.doi.org/10.1364/AO.51.006489
I’m in my seventh season of volunteer lifesaving with Queenscliff Lifesaving Club and have received a scholarship to assist with my PhD studies from the club based on the generous support of John Cunningham of Cunningham’s Real Estate on Sydney’s Northern Beaches