Postgraduate Course: Imaging: Digital image processing and analysis (NEME11020)
Course Outline
| School | Deanery of Clinical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This optional course will address in detail the processing and analysis of digital data derived in the imaging environment, including sampling and quantization, perception and modeling, validation techniques, registration techniques, voxel based analysis, and segmentation as well as storage, protection, archiving and mining of image data. |
| Course description |
Under development - will be listed explicitly on the Imaging MSc website at http://www.imagingmsc.ed.ac.uk
Proposed Modules will cover but not be limited to:
+ Sampling and quantisation
+ Perception and modelling
+ Computational modelling
+ Validation techniques
+ Registration techniques
+ Voxel based analysis
+ Segmentation
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
| Not being delivered |
Learning Outcomes
| See course description
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Reading List
| Under development - will be listed for each module in the online environment with links directly to University library holdings. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Special Arrangements |
All courses to be delivered online by distance learning, using the institutional learning environment and other online tools (e.g. wiki, objective testing software), accessed by using the standard university EASE login. |
| Keywords | Processing, Analysis, Digital data, Sampling, Quantization, Perception, Modeling, Validation, Regist |
Contacts
| Course organiser | Prof Andrew Farrall
Tel: (0131) 537 3910
Email: andrew.farrall@ed.ac.uk |
Course secretary | Dr Charilaos Alexakis
Tel: 0131 537 3125
Email: C.Alexakis@ed.ac.uk |
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