Module 22313 (2011)
Syllabus page 2011/2012
06-22313
Computational Tools for Modelling and Analysis
Level 4/M A
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
None.
Outline
The module introduces concepts, techniques and tools for the computational modelling and analysis of image-derived data. The key schemes for data representation, and a survey of state-of-the art methods for statistical data analysis, stochastic modelling, machine learning and optimisation, will be presented in context of imaging processes (e.g. stochastic nature of the photon-matter interaction; optimisation of parameters of an imaging system) and image-derived data (e.g. factor analysis, Markov Chain modelling, cluster analysis, pattern recognition to identify "hidden" patterns in data). The individual topics will be presented by leading researchers from Computer Science. The module will also provide practical experience of using a subset of the techniques, implemented in Matlab. These laboratory/exercise class sessions necessitate and give rise to the higher formal contact hours for this module when compared to some other PSIBS modules.
Aims
The aims of this module are to:
- To be completed
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | explain the principles of the main methods for statistical data analysis, stochastic modelling, machine learning and optimisation and explain (and communicate) their advantages and limitations | |
| 2 | identify, justify and apply suitable analysis, modelling and optimisation techniques to image-derived data originating from biomedical research problems | |
| 3 | implement solutions in Matlab and critically appraise which analysis approaches should be used for a given kinds of problems | |
Restrictions, Prerequisites and Corequisites
Restrictions:
Compulsory for PhD with Integrated Studies in Physical Sciences of Imaging in the Biomedical Sciences
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
Lectures, seminars, laboratory / exercise classes
Contact Hours:
Assessment
- Sessional: Portfolio of exercise/laboratory reports: 30%. Structured written unseen examination of 1.5 hours organised by School: 70%.
- Supplementary (where allowed):
Recommended Books
None
Detailed Syllabus
Not applicable
Last updated: 5 September 2011
Source file: /internal/modules/COMSCI/2011/xml/22313.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus