Course Title: Biomedical Signal and Image Processing

Part A: Course Overview

Course Title: Biomedical Signal and Image Processing

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

OENG1105

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2016

OENG1136

Bundoora Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020

Course Coordinator: Prof. Margaret Lech

Course Coordinator Phone: +61 3 9925 1028

Course Coordinator Email: margaret.lech@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

It is desirable but not compulsory to have completed

•EEET2369 Signals and Systems 1

•EEET2494 Biomedical Signal Analysis

or equivalent before commencing this course.

It is also desirable to have basic 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 (www1.rmit.edu.au/browse;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

Course activities will provide a mixture of lectures, practical laboratory exercises, and progress assessment tests.

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

Weekly laboratory assignments will help you to develop problem-solving skills and provide systematic feedback on your progress.

Laboratory and progress tests are designed to develop 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 guide to your study on Canvas.

•PowerPoint slides and video recordings of lectures.

•Instructions and video recordings of lectures and assignments.

•Access to Matlab software.

•Consultations and meetings with Course Coordinator via video links.

•Access to the university library resources.

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: Image Processing Test
Total Weighting 40%
This assessment task is split into 3 parts
Part 1 in Week 3 (10%)
Part 2 in Week 5 (15%)
Part 3 in Week 7 (15%)
This assessment task supports CLOs 1, 2, 4, 5 and 6

Assessment Task 2: Signal Processing Test
Total Weighting 30%
This assessment task is split into 2 parts
Part 1 in Week 9 (15%)
Part 2 in Week 11 (15%)
This assessment task supports CLOs 1, 2, 4, 5 and 6

Assessment Task 3: Laboratory Work and Reports
Total Weighting 30%
This assessment task supports CLOs 3 & 6 & 7