Course Title: Biomedical Signal and Image Processing

Part A: Course Overview

Course Title: Biomedical Signal and Image Processing

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


125H Electrical & Computer Engineering


Sem 2 2016


Bundoora Campus


172H School of Engineering


Sem 2 2017,
Sem 2 2018

Course Coordinator: Assoc. Prof. Margaret Lech

Course Coordinator Phone: +61 3 9925 1028

Course Coordinator Email:

Pre-requisite Courses and Assumed Knowledge and Capabilities

You are expected to have successfully completed   

  • EEET2369 Signals and Systems 1
  • EEET2494 Biomedical Signal Analysis

or equivalent before commencing this course.

It is also assumed that you have Matlab and/or C/C++ programming skills.

Course Description

Biomedical Signal and Image Processing will introduce you to biomedical applications of image enhancement, image restoration, adaptive filtering of audio signals, psychoacoustics and speech analysis.

The theory presented in the lectures will be applied to solve practical problems laboratory sessions. The laboratory assignments will introduce highly advanced medical and biomedical imaging and analysis methodology using Matlab biomedical signal processing tools.

Particular topics to be investigated include:

1. Introduction to biomedical image processing

2. Colour images

3. Image filtering

4. Image enhancement and de-blurring

5. Image restoration

6. Image segmentation and edge detection

7. Adaptive filtering and source separation

8. Psychoacoustics and hearing aids

9. Speech production and analysis

Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. (This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onwards. See the WAM information web page for more information (;ID=eyj5c0mo77631).

Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes of the Bachelor of Engineering (Honours):

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources.

On completion of this course you should be able to:

  1. Explain basic concepts of biomedical image processing
  2. Explain principles of image enhancement, segmentation, filtering and restoration
  3. Apply image processing techniques to basic biomedical applications
  4. Explain principles of hearing aids design
  5. Explain and apply principles of audio signal separation in the context of medical applications
  6. Design and test image and signal processing algorithms
  7. Communicate your designs and test findings through oral and written reports.

Overview of Learning Activities

Weekly 4-hours study activities will provide a mixture of lectures, practical laboratory exercises and progress assessment tests.

Key concepts and their application will be explained in power point presentations. , with practice examples used to demonstrate possible solutions.  

The weekly homework exercises implemented as blackboard self-tests will help you to develop problem solving skills and provide systematic feedback on your progress.

Laboratory assignment work is designed to develop your group and communication skills through written reports, and to guide you through a real-world design and verification methodology.

Overview of Learning Resources

All learning resources for this course are available on the blackboard university online system.

These resources include:

  • Weekly step by step guidance how to proceed with your study
  • Theoretical module including power point slides explaining important topics and ideas
  • Laboratory assignment instruction module including written explanations and video recorded instructions
  • Access to laboratory with complete Matlab software package
  • Access to Matlab software that you can install on your own computer

Laboratory assignment work has been designed to develop your group and communication skills through written reports, and to guide you through a real-world design and verification methodology.

Overview of Assessment

☒This course has no hurdle requirements.

☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Leaning & Teaching).

Assessment tasks


Assessment Task 1: Weekly progress online tests

Weighting 70%

This assessment task supports CLOs 1, 2, 4, 5 and 6

Assessment Task 2: Laboratory work and reports (Week2)  

Weighting 30%

This assessment task supports CLOs 3 & 6 & 7