Statistical Bioinformatics Seminar: David Waddington

Speaker: David Waddington 

Abstract: Real-time tumour targeting with MRI-guidance has
recently become possible with the advent of the MRI-Linac, which combines the unrivalled
image quality of MRI with a linear accelerator (Linac) for x-ray radiation therapy.
However, the relatively low spatio-temporal resolution of real-time MRI reduces the
accuracy with which radiation beams can be adapted to tumour motion (e.g.
respiration).  New low-latency imaging techniques are thus essential to improving the
quality of MRI-Linacs treatments.  In this seminar, I will describe
artificial-intelligence-based tools we have developed that can improve target tracking
during radiation treatments.  I will discuss the successes we have had ( and the
challenges faced) in deploying these AI tools to clinical systems.  

Bio: Dr David Waddington is an NHMRC Emerging Leadership Fellow at the Image X Institute
in the Faculty of Medicine and Health at the University of Sydney.  As an early career
researcher (PhD(Science), The University of Sydney, 2018), he specializes in developing
new imaging technologies based on Magnetic Resonance Imaging (MRI) that can be used for
the targeting of cancer therapeutics.  David has published high impact, first-author
research articles in multidisciplinary journals including Nature Communications and
Science Advances that have led to two patent applications.  He has been the recipient of
prestigious academic awards including a 2013-14 Postgraduate Fulbright Scholarship
(Harvard University) and a University Medal in Physics (UNSW - 2010).  His work has won
international conference prizes including two Best in Physic sat the American
Association of Physicists in Medicine (AAPM - 2020, 2022) and two Summa Cum Laude awards
at the International Society of Magnetic Resonance in Medicine (ISMRM - 2016, 2020).
David has given several invited talks at international imaging conferences and presented
at public events such as TEDx.