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Course Catalog 2010-2011
BME-2636 Medical Image Analysis, 5 cr |
Person responsible
Hannu Eskola
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Accepted assignments and final exam.
Completion parts must belong to the same implementation
Learning outcomes
After completing the course students can recognize different image processing methods applicable for each type of clinical image. Students can explain most common image analysis methods, which are used for clinical diagnosis. Students can perform basic medical image analysis with Matlab.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Fundamentals of medical images and of medical image processing. | ||
| 2. | Image segmentation methods. | ||
| 3. | Image analysis methods: Tissue characterization, 4D image analysis. | ||
| 4. | Visualization methods. | ||
| 5. | Image registration methods. |
Evaluation criteria for the course
The final mark is based on final exam grade (60%) and assignments grade (40%).
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | Digital Image Processing for Medical Applications | Dougherty, G. | English | ||||
| Lecture slides | Lecture notes. | English |
Prerequisites
| Course | Mandatory/Advisable | Description |
| LTT-3106 Medical Imaging Methods | Advisable | |
| SGN-3016 Digital Image Processing I | Advisable |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
| Course | Corresponds course | Description |
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Additional information
Suitable for postgraduate studies
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| Lectures Other contact teaching |
Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 % |