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Physical Sciences Module 1: Introductory Science and Methods (ANIM0003)

Key information

Faculty
Faculty of Brain Sciences
Teaching department
UCL Queen Square Institute of Neurology
Credit value
15
Restrictions
N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module aims to help you engage with more complex technical material delivered later in the Advanced Neuroimaging course by introducing you to essential concepts in Mathematics, Physics and IT relating to Neuroimaging research.Ìý
The module also gives you an introduction to Statistics to help you critically appraise journal articles and to make good choices while developing study designs for your Research Projects.
Finally, the module introduces the main principles of Image Formation and will allow you to develop your coding skills using MATLAB for numerical calculation, data analysis & display - you will no doubt find this an invaluable tool for your future research.
At the end of this module, students will be able to…
1. Core Mathematics (CM)
1.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDemonstrate understanding of and competence in the basic mathematics of imaging science, such as vectors, matrices, exponential functions, periodic functions, complex numbers and Fourier analysis.Ìý
2. Core IT (CIT)
2.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDescribe the basic architecture of modern computer systems, hardware and software.
2.02: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýUse decimal and binary approaches to represent data and compare different approaches to the compression of data
2.03: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDiscuss the key features of medical image metadata and Digital Image Communications in Medicine (DICOM) and the role they play in medical imaging
3. Matlab (ML)
3.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýUnderstand, design and code programs in the Matlab programming environment, executing tasks relating to the Core Mathematics learning outcomes.
4. Principles of Image Formation (PIF)
4.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDescribe the basic principles of image formation relevant to modern neuroimaging.
4.02: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDescribe the basic concepts of image perception and representation, digital images and basic digital image transformations.
5. Core Physics (CP)
5.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDemonstrate a knowledge of the necessary background physics required for the remaining course units, including essential wave behaviour, electricity and magnetism, atomic structure and radiation.
6. Introductory Statistics (S)
6.01: Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýDemonstrate understanding of the basic statistical methods required to carry out independent research in the field of Neuroimaging.
6.02: Ìý ÌýList and describe the basic concepts in statistics that are required in Artificial Intelligence.

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
100% Exam
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
0
Module leader
Dr Adam Liston
Who to contact for more information
c.routh@ucl.ac.uk

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

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Exam
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
12
Module leader
Dr Adam Liston
Who to contact for more information
c.routh@ucl.ac.uk

Last updated

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

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