• Offered by RS Electrical, Energy and Materials Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering
  • Academic career UGRD
  • Mode of delivery In Person

This course will only be offered from 2022

This course covers the concepts behind analysing and processing signals and images of a biological system, including in 1D, 2D and 3D. Being able to interpret and respond to the variability of biomedical signals is key to many modern devices including ECG, pace-makers, life support systems, stress monitors, and cochlea and visual prostheses. The rapid processing of bio-signals and biomedical images is used in a wide range of diagnostic and interactive medical applications including wearable electrocardiograms, image guided surgery and disease diagnosis. This course introduces and explores concepts of analysing and processing images of biological systems using advanced mathematics. The course will examine the mathematical concepts of low-level signal and high dimensional image processing/analysis (e.g., enhancement and segmentation), and move to quantitative processing such as registration and diagnosis. The course will examine these in the context of a broad range of medical signals and images, such as heart monitors, ultrasound, CT, MRI and microscopy.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Understand how biosignals (after acquisition) are processed in one and higher dimensions.
  2. Demonstrate advanced knowledge of biomedical signal and image processing methods by being able to describe the theory and mathematics.
  3. Demonstrate an understanding of signal representation and processing across a range of biomedical devices.
  4. Apply advanced knowledge in biomedical image processing to develop and implement biomedical algorithms for processing biomedical images and critically interpret their success.
  5. Understand what biomedical signals are, the different noise analysis methods, and how contrast can be enhanced using advanced mathematical methods.
  6. Demonstrate an understanding of the role of biomedical signal and image processing medical devices that is adaptable to a range of technologies.

Indicative Assessment

  1. Research and Design Project (30) [LO null]
  2. Labs (20) [LO null]
  3. Final Exam (50) [LO null]

In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle. 

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Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have successfully completed ENGN2219 and ENGN3820.

Minors

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2020 $4320
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

There are no current offerings for this course.

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