Study As
Full Time

Principal Supervisor
Associate Professor Sang-Heon Lee

Main Campus
Mawson Lakes

Applications Close
16 Dec 2022

Study Level

Applications Open To
Domestic Candidate

Tuition Fees:
All domestic students are eligible for a fee waiver. International students who receive a stipend are eligible for a fee waiver. Find out more about fees and conditions.

Project Stipend:
$28,854 p.a. available to domestic applicants only

Develop machine learning methods for classifying liver disease

If you’re motivated to build a career in machine learning and keen to contribute new knowledge in radiology, the University of South Australia – Australia’s University of Enterprise – is offering an industry partnered, project-based PhD in partnership with Adelaide MRI.

Liver disease affects 30% of the world population, causing 2 million deaths per year. Traditional diagnosis methods either carry additional health risks (biopsy) or are not accurate enough (manual analysis of medical images). Although liver biopsy is still the gold standard for diagnosis, the imaging method has been well accepted as a non-invasive alternative. 

Ultrasonography and CT images are the preferred non-invasive options. However, the speed and accuracy of diagnosis depends solely on a doctor’s experience, competency, and capability to analyse the characteristics of liver diseases. 

Even though some machine learning techniques have the potential to assist with diagnostic decisions, this method requires rigorous validation. We also need to prove that it is more time efficient and consistent than current methods.  

The project aims to develop an integrated diagnostic machine learning classifier for liver diseases, by analysing medical CT images, identifying abnormalities, and providing a consistent reporting process for radiologist. 

Our industry partner, Adelaide MRI, will provide the CT images of liver diseases, catalogued with unique labels. Using these images, we can develop an integrated diagnostic machine learning classifier for liver diseases. We expect that this result will provide a significant breakthrough for radiologists and we anticipate that the algorithm can easily be extended to other organs, such as lung, heart, and spleen.

You would participate in and contribute to identifying the medical features associated with the potential parameters required for diagnosing health issues in CT scan images of the liver, including automatic segmentation around the boundaries of liver. You will also assist with developing a machine learning algorithm to classify liver diseases for accurate/fast diagnosis and developing a data mining algorithm to identify most suitable templates of cases available in the database for fast/consistent reporting. 

In this industry engaged PhD, you will also take up an internship placement with Adelaide MRI, to validate the outcome within a real clinic environment.

 What you’ll do

In this project-based research degree, you will develop a comprehensive understanding of machine learning algorithms, strong expertise in medical image processing and sound understanding in medical radiological reporting processes, with hands-on practice using MATLAB and Python.

Supervisory Team 
Financial Support 

This project is funded for reasonable research expenses.  Additionally, a living allowance scholarship of $28,854 per annum is available to Australian and New Zealand citizens, and permanent residents of Australia, including permanent humanitarian visa holders.  Australian Aboriginal and/or Torres Strait Islander applicants will be eligible to receive an increased stipend rate of $45,076 per annum. A fee-offset or waiver for the standard term of the program is also included.  For full terms and benefits of the scholarship please refer to our scholarship information. International applicants are not invited to apply at this time.

An additional top-up scholarship may be available to the preferred applicant with additional financial support for equipment and other research related costs by the industry partner (subject to finalized agreement).

Eligibility and Selection 

This project is open to applications from Australian or New Zealand citizens, and Australian permanent residents or permanent humanitarian visa holders. International applicants are not invited to apply at this time.

Applicants must meet the eligibility criteria for entrance into a PhD. Additionally applicants must meet the projects selection criteria:

  • programming and image processing background 
All applications that meet the eligibility and selection criteria will be considered for this project. A merit selection process will be used to determine the successful candidate.

The successful applicant is expected to study full-time and to be based at our Mawson Lakes Campus in the north of Adelaide.

Essential Dates 

Applicants are expected to start in a timely fashion upon receipt of an offer.  Extended deferral periods are not available. Applications close on Friday, 16th December.

How to apply:

Applications must be lodged online, please note UniSA does not accept applications via email.

For further support see our step-by-step guide on how to apply , or contact the Graduate Research team on +61 8 8302 5880, option 1 or email us at You will receive a response within one working day.

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