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Computing in Medicine (MPHY0020)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
Medical Physics and Biomedical Engineering
Credit value
15
Restrictions
N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

From electronic patient records to state-of-the-art medical image acquisition and analysis, computing and digital signal processing are vital techniques in modern medicine. This module is designed to introduce important topics in computing, with special emphasis given to the application of computing methods in a medical context.

This module consists of three parts: Introduction to Computing in Medicine, Introduction to MATLAB Programming, and Digital Signal and Image Processing. Students completing this course will have learned the following skills:

Introduction to Computing in Medicine:

  • Identify and explain the function of key components of a modern computer
  • Describe the major uses of computers in a healthcare setting (e.g. PACS)
  • Explain key regulatory, legal, and ethical principles of medical data security and protection
  • Represent numbers using different binary number representations (e.g. floating point)
  • Demonstrate an understanding of statistics describing decisions or tests

Introduction to MATLAB Programming:

  • Demonstrate an understanding of the fundamental concepts of computer programming, including recommending appropriate data types for different forms of data
  • Demonstrate a working knowledge of basic MATLAB commands
  • Write a MATLAB program to perform simple analysis and visualisation of biomedical data

Digital Signal and Image Processing:

  • Demonstrate an understanding of the principles and application of key elements of digital signal processing, including: sampling theory, quantisation, representing a signal in both the time/space and frequency domains, convolution, the Discrete Fourier Transform, and representing and storing binary data
  • Demonstrate an understanding of the principles and application of key elements of image processing, including: greyscale and colour images, linear filtering, edge detection, computing gradients, interpolation, morphological filters, and an introduction to image segmentation and registration

This module is assessed by written examination (66%) and coursework (34%) in the form of a MATLAB programming assignment.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
Online
Methods of assessment
66% Fixed-time remote activity
34% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
0
Module leader
Dr Erwin Alles
Who to contact for more information
medphys.teaching@ucl.ac.uk

Intended teaching term: Term 1 ÌýÌýÌý Undergraduate (FHEQ Level 6)

Teaching and assessment

Mode of study
In person
Methods of assessment
66% Fixed-time remote activity
34% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
49
Module leader
Dr Erwin Alles
Who to contact for more information
medphys.teaching@ucl.ac.uk

Intended teaching term: Term 1 ÌýÌýÌý Undergraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
66% Fixed-time remote activity
34% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
31
Module leader
Dr Erwin Alles
Who to contact for more information
medphys.teaching@ucl.ac.uk

Intended teaching term: Term 1 ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
66% Fixed-time remote activity
34% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
36
Module leader
Dr Erwin Alles
Who to contact for more information
medphys.teaching@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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