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3D Patient Assessment: 3D machine learning to calculate total burn surface area

Study level

PhD

Master of Philosophy

Honours

Vacation research experience scheme

Faculty/Lead unit

Topic status

We're looking for students to study this topic.

Supervisors

Dr Sean Powell
Position
Postdoctoral Research Fellow (AQF)
Division / Faculty
Science and Engineering Faculty

Overview

The future of healthcare involves the application of 3D and computational technologies throughout the entire patient journey. This project involves developing technology, software and processes to enable automated measurements of total burn surface area.

It is important for treatment planning and medication dosage calculations that the burn surface area is determined. Currently, this is estimated using visual inspection or roughly indicating the burned regions on an image.

3D scanning and computer vision offers the ability to automatically determine the burned tissue regions from 3D models of the patient.

This project involves working with clinicians and researchers to source training material for machine learning systems and coordinating with computer vision scientists to determine the best approaches. It also involves searching through literature to find existing approaches to this problem and developing ways to implement the best available techniques to 3D surfaces rather than just images.

Research activities

As a part of this project, you will be involved in:

  • selecting the optimal machine learning network design for 3D image segmentation
  • sourcing or designing methods for labeled training data
  • working with hospitals and medical research institutes to obtain images of patient burn injuries
  • developing optimal ways to label burn injury images.

Keywords

Contact

Contact the supervisor for more information.