Last modified: 23 Jul 2024 11:07
A study of computing and information technology as applied to medical physics and medical imaging. The aims of the course are: to introduce students to the applications of computing in a clinical context; to develop knowledge and skills in basic data management and medical image processing; to provide familiarity with standard data formats, networking and security in medicine; to introduce legal and safety aspects of information management in medicine and to introduce the principles of computer programming in a practical environment.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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Information Technology is at the heart of Medical Physics and Medical Imaging. From the formation of 3D images to the storage, retrieval and subsequent processing of the images to generate diagnostically useful information. This course provides an introduction to computing and information technology as applied to medical physics and medical imaging, including an introduction to medical image processing techniques. Hands-on learning is provided to build confidence with computer software.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 66 | |
|---|---|---|---|---|
| Assessment Weeks | 40 | Feedback Weeks | 44 | |
| Feedback |
Since this is the final assessment for the course feedback will typically be provided (in person) to students who need to prepare for a resit. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Evaluate | Describe the principles underpinning image registration, segmentation and fusion as applied to multimodality imaging and image guided procedures. |
| Procedural | Analyse | Appraise security and legislative considerations relating to the electronic storage and transfer of clinical data such as images and patient records. |
| Procedural | Analyse | Analyse parameters that determine the nature and quality of a digital image, such as sampling theory, acquisition rates, and image display quality. |
| Procedural | Apply | Relate the concepts of spatial, temporal, and contrast resolution in medical imaging to outcomes for clinical reporting. |
| Procedural | Create | Demonstrate competence in the ability to use programming/modelling packages. |
| Procedural | Evaluate | Evaluate outcomes of common manipulation techniques on medical images such as compression, translation, rotation, scaling, Fourier transform, averaging, and noise reduction. |
| Assessment Type | Summative | Weighting | 17 | |
|---|---|---|---|---|
| Assessment Weeks | 30 | Feedback Weeks | 32 | |
| Feedback |
Class Test (Online) Feedback on answers provided through MyAberdeen. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Analyse parameters that determine the nature and quality of a digital image, such as sampling theory, acquisition rates, and image display quality. |
| Procedural | Apply | Relate the concepts of spatial, temporal, and contrast resolution in medical imaging to outcomes for clinical reporting. |
| Procedural | Create | Demonstrate competence in the ability to use programming/modelling packages. |
| Procedural | Evaluate | Evaluate outcomes of common manipulation techniques on medical images such as compression, translation, rotation, scaling, Fourier transform, averaging, and noise reduction. |
| Assessment Type | Summative | Weighting | 17 | |
|---|---|---|---|---|
| Assessment Weeks | 33 | Feedback Weeks | 35 | |
| Feedback |
Discussions are ongoing with eLearning around integration of Matlab Grader into Blackboard, which will allow for some automation of grading. Most of the integration is now complete, but we are just finalising details around student privacy and ongoing support. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Evaluate | Describe the principles underpinning image registration, segmentation and fusion as applied to multimodality imaging and image guided procedures. |
| Procedural | Analyse | Analyse parameters that determine the nature and quality of a digital image, such as sampling theory, acquisition rates, and image display quality. |
| Procedural | Apply | Relate the concepts of spatial, temporal, and contrast resolution in medical imaging to outcomes for clinical reporting. |
| Procedural | Create | Demonstrate competence in the ability to use programming/modelling packages. |
| Procedural | Evaluate | Evaluate outcomes of common manipulation techniques on medical images such as compression, translation, rotation, scaling, Fourier transform, averaging, and noise reduction. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | 46 | Feedback Weeks | 48 | |
| Feedback |
Since this is the resit (and therefore final assessment) feedback would typically only be provided (in person) if a student were to be granted a further attempt on appeal. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Appraise security and legislative considerations relating to the electronic storage and transfer of clinical data such as images and patient records. |
| Procedural | Create | Demonstrate competence in the ability to use programming/modelling packages. |
| Procedural | Apply | Relate the concepts of spatial, temporal, and contrast resolution in medical imaging to outcomes for clinical reporting. |
| Procedural | Analyse | Analyse parameters that determine the nature and quality of a digital image, such as sampling theory, acquisition rates, and image display quality. |
| Procedural | Evaluate | Evaluate outcomes of common manipulation techniques on medical images such as compression, translation, rotation, scaling, Fourier transform, averaging, and noise reduction. |
| Conceptual | Evaluate | Describe the principles underpinning image registration, segmentation and fusion as applied to multimodality imaging and image guided procedures. |
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