Radiomics for cancer diagnosis and patient outcome prediction
adiomics is an emerging field that aims to extract vital information from growing collections of medical imaging and patient data. A large number of quantitative features are extracted from medical images, from basic features such as shape and size to more advanced texture analysis metrics. Radiomic signatures are constructed from these features across a patient cohort and are being investigated for tumor staging, treatment response and patient outcome prediction.
Whilst a range of radiomics feature analysis tools are available through the research community, a bottleneck for many studies is manual contouring or segmentation of the tumor volume. We propose the application of Deep Learning, which has recently shown excellent performance in many image analysis tasks, to develop an auto-contouring tool. Such a tool would automate our radiomics analysis and allow us to mine a much larger portion of the existing medical image database.
The project would suit a student with a background in medical imaging and analysis. The initial project has potential to focus on MRI data and developing a prediction model for brain tumors.
Physical Sciences Research: Medical physicists play a key role in underpinning high quality medical imaging and the planning and delivery of radiation therapy treatments at Peter Mac. We collaborate extensively with oncologists, radiation therapists, laboratory researchers, imaging scientists and cancer surgeons. A major strength of our research program is the ability of our medical physicists and biomedical engineers to turn ideas into evidence-based clinical practice. This has led to many successful innovations such as a computer controlled rotating turntable for whole body electron treatments, artificial intelligence for organ segmentation and image analysis, tools to ensure high quality clinical trials and the development of a device for tracking retinal motion during radiotherapy.
Peter MacCallum Cancer Centre, Melbourne Australia
Peter MacCallum Cancer Centre is Australia’s only public hospital solely dedicated to cancer, and home to the largest cancer research group in Australia. Cancer is a complex set of diseases, and modern cancer research institutes such as Peter Mac conduct research covering a diversity of topics that range from laboratory-based studies into the fundamental mechanisms of cell growth, translational studies that seek more accurate cancer diagnosis, clinical trials with novel treatments, and research aimed to improve supportive care.
All students engaged in postgraduate studies at Peter Mac are enrolled in the Comprehensive Cancer PhD (CCPhD) program, regardless of which university they are enrolled through. The program is managed by the Sir Peter MacCallum Department of Oncology (The University of Melbourne), based at Peter Mac.
Tapping into the depth and breadth of knowledge and experience offered by the ten partners of the Victorian Comprehensive Cancer Centre (VCCC) alliance, the University of Melbourne’s Comprehensive Cancer PhD Program provides a unique opportunity for multidisciplinary cancer-related PhD candidates to experience clinical and research activities across the alliance.
The Comprehensive Cancer PhD program builds on established conventional training for cancer research students providing a coordinated program of skills, research and career training in addition to usual PhD activities. The program is designed to complement existing PhD activities and provides opportunities to develop professional skills that will help candidates to fulfil their career ambitions.
All PhD students at Peter Mac must have a scholarship from The University of Melbourne or through another government, trust or philanthropic organisation. Before applying for a scholarship, you must have agreed on a project with an institute supervisor.
For further information about the university application process, see:
For further information regarding scholarships (both local and international), see:
Closing dates for applications for scholarships to commence in 2019: Round 1 -31 October 2018; Round 2 - 28 Nov 2018; Round 3 - 20 Feb 2019.