Machine learning assisted stroke neuroimaging

Research Opportunity
PhD, Masters by Research
Number of Honour Places Available
1
Number of Master Places Available
1
Department
Medicine and Radiology
Primary Supervisor Email Number Webpage
Professor Bernard Yan bernard.yan@mh.org.au 93492477 Personal web page
Co-supervisor Email Number Webpage
Professor Marimuthu Palaniswami palani@unimelb.edu.au Personal web page

Summary Assessment of stroke neuroimaging is increasingly complex. Machine learning assisted (decision support system) will likely enhance clinical decision making to the greater benefit of stroke patients.

Project Details

Neuroimaging of acute stroke and other cerebrovascular disease involves advanced modalities including CT perfusion and MRI. Assessment of images generated by advanced modalities is subject to significant inter-rater disagreement, leading to errors in clinical decision making. This is compounded by the variable levels of expertise in clinical staff especially in the rural regions.

Machine learning takes advantage of training algorithms to "read scans like an expert" by iterative procedures involving large data sets. We have been working in this field for some years and have developed the infrastructure to test and validate novel algorithms. The aim is to develop machine learning assisted tools to remove inter-rater disagreement and improve prediction of clinical outcomes after stroke.




Research Opportunities

PhD, Masters by Research
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research

Graduate Research application

Honours application

Key Contact

For further information about this research, please contact a supervisor.

Department

Medicine and Radiology


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