Module 22312 (2013)
Module Description - Imaging and Image Analysis
The Module Description is a strict subset of the Syllabus Page, which gives more information
| Module Title | Imaging and Image Analysis | ||||||||||||
| School | Computer Science | ||||||||||||
| Module Code | 06-22312 | ||||||||||||
| Descriptor | COMP/06-22312/LM | ||||||||||||
| Member of Staff | Hamid Dehghani | ||||||||||||
| Level | M | ||||||||||||
| Credits | 10 | ||||||||||||
| Semester | 1 | ||||||||||||
| Pre-requisites | None | ||||||||||||
| Co-requisites | None | ||||||||||||
| Restrictions | Compulsory for PhD with Integrated Studies in Physical Sciences of Imaging in the Biomedical Sciences. | ||||||||||||
| Contact hours | |||||||||||||
| Delivery | Lectures, seminars, exercise/laboratory classes and small group discussions | ||||||||||||
| Description | This module introduces the selected theoretical aspects of imaging sciences, methods of image formation, image analysis methods and practical imaging systems together with their leading-edge applications in biomedical sciences. The stress is on developing an understanding of the generic concepts underpinning the physical processes of imaging, and their practical realisations in specific imaging modalities and imaging systems. The theoretical coverage will include the necessary mathematical tools (e.g. linear systems, Fourier analysis, statistical distributions, Bayes analysis), physics concepts (e.g. wave equations, energy transport, photon counting, noise modelling) and image formation models (e.g. detection and measurement, error propagation, direct and indirect techniques, image reconstruction, parameter estimation). The coverage of practical image analysis techniques will include image segmentation, feature extraction, motion and optic flow analysis, and image classification, with focus on constructing working solutions for specific biomedical image analysis. Topics related to specific imaging modalities and applications will be presented by experts from the University and industry. The module will 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. | ||||||||||||
| Outcomes |
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| Assessment | Sessional: continuous assessment (portfolio of laboratory/exercise coursework) (30%), Oral examination (70%) Supplementary (where allowed): | ||||||||||||
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