Study-Unit Description

Study-Unit Description


CODE SCE5021

 
TITLE Introduction to Biomedical Signal and Image Processing

 
LEVEL 05 - Postgraduate Modular Diploma or Degree Course

 
ECTS CREDITS 5

 
DEPARTMENT Systems and Control Engineering

 
DESCRIPTION Biomedical signal and image processing plays a crucial role in the acquisition, analysis and processing of biomedical data. The use of signal and image processing techniques is ubiquitous in modern clinical tools and is essential for enhancing the quality of the acquired physiological signals and images. Biomedical signal and image processing also allows for the extraction of features that are useful for proper diagnosis, treatment and rehabilitation.

Study-unit Aims:

1. To help students acquire an understanding of fundamental signal and image processing techniques necessary for the analysis and processing of biomedical data in the form of signals and images.

2. To help students:
a. Appreciate the origin and nature of biomedical signals.
b. Understand and apply the following signal processing and image processing principles:
- signal sampling and quantisation;
- generation of digital images;
- Fourier analysis of signals and images;
- frequency domain analysis of signals and images;
- intensity transformations of digital images;
- filtering of digital signals in the time and frequency domain;
- filtering of digital images in the spatial and frequency domain.

3. To train students in the use of appropriate signal processing and image processing software.

Learning Outcomes:

1. Knowledge & Understanding:
By the end of the study-unit the student will be able to:

- describe the origin and nature of biomedical signals and images;
- describe the processes of sampling and quantisation involved in the digitisation of signals and images;
- describe how the spectral representation of signal and images can be obtained through Fourier analysis;
- explain how the magnitude and phase characteristics of the spectral representation relate to the temporal or spatial characteristics of a signal or image, respectively;
- explain how different intensity transformations affect an image;
- explain how signal and image filtering is carried out;
- describe how frequency domain filtering of signals can be carried out and how this relates to time domain filtering;
- describe how frequency domain filtering of images can be carried out and how this relates to spatial domain filtering.

2. Skills:
By the end of the study-unit the student will be able to:

- carry out spectral analysis on a digital signal in order to extract the magnitude and phase characteristics of a signal;
- carry out spectral analysis on a digital image in order to extract the magnitude and phase characteristics of an image;
- perform intensity transformations to enhance the characteristics of an image;
- perform digital signal filtering to remove unwanted signal components and/or enhance components of interest;
- perform digital image filtering to remove unwanted image components and/or enhance components of interest;
- implement spectral analysis, intensity transformation, and filtering techniques using Matlab.

Main Text/s and any supplementary readings:

Digital Signal Processing: Principles, Algorithms and Applications. John G. Proakis & Dimitris G. Manolakis. Pearson Prentice Hall.
Digital image processing. Rafael C. Gonzalez and Richard E. Woods. Pearson.

 
STUDY-UNIT TYPE Lecture, Independent Study & Tutorial

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Resit Availability Weighting
Assignment SEM2 No 30%
Examination (2 Hours) SEM2 Yes 70%

 
LECTURER/S Stefania Cristina
Owen Falzon

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2020/1. It may be subject to change in subsequent years.

https://www.um.edu.mt/course/studyunit