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We are aiming for an incremental return to campus in accordance with guidelines provided by NSW Health and the Australian Government. Until this time, learning activities and assessments will be planned and scheduled for online delivery where possible, and unit-specific details about face-to-face teaching will be provided on Canvas as the opportunities for face-to-face learning become clear.

We are currently working to resolve an issue where some unit outline links are unavailable. If the link to your unit outline does not appear below, please use the link in your Canvas site. If no link is available on your Canvas site, please contact your unit coordinator.

Unit of study_

ELEC5622: Signals, Software and Health

This unit is related to health informatics and focuses on introducing the acquisition, processing, and analysis of medical imaging signals. It introduces multiple widely used medical imaging techniques such as MRI, diffusion MRI, X-ray, and CT, as well as both the conventional and deep learning based image processing and machine learning methods to analyse medical image data for diagnosis. During the course, some commonly used software and platforms for medical image analysis, especially for brain image analysis, will also be covered.

Code ELEC5622
Academic unit Electrical and Information Engineering
Credit points 6
Prerequisites:
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None
Corequisites:
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None
Prohibitions:
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None
Assumed knowledge:
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Mathematics (linear algebra and probabilities) and basic programming skills (python/matlab/C++/java)

At the completion of this unit, you should be able to:

  • LO1. use appropriate software platforms to process and analyse medical imaging signals
  • LO2. explain the principles of common medical imaging techniques and understand the foundations of how 3D medical images are formed from these signals.
  • LO3. understand and apply the common techniques for medical image processing and analysis, including both the conventional and the deep learning based methods.
  • LO4. use the existing medical image processing and machine learning toolboxes for medical image analysis.
  • LO5. write professional technical reports and make presentations to communicate complex materials in clear and concise terms.
  • LO6. develop basic team work and project management skills through a group project

Unit outlines

Unit outlines will be available 2 weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.

There are no unit outlines available online for previous years.