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SGN-3507 Introduction to Medical Image Processing, 5 cr |
Ulla Ruotsalainen
Lecture times and places | Target group recommended to | |
Implementation 1 |
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To pass the course the student has to make all the computer exercises, pass the exam and make a small assignment.
Completion parts must belong to the same implementation
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The outcome of the course is that the students will have skills and knowledge on the tomography imaging in the field of medicine. Moreover, the students will gain basic knowledge on multimodal image registration and image segmentation.
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Basic principles of the image reconstruction methods in tomography imaging. Radon transformation, Backprojection (BP), Filtered Backprojection (FBP), Maximum Likelihood Expectation Maximization (MLEM). | Ordered Subset EM, noise penalizations (one step late and MRP) | Mathematical derivations of the reconstruction methods |
2. | Image coregistration for medical use, problems and image fusion techniques. | ||
3. | Structural imaging versus functional imaging in the view of automatic analysis of the image sets. | ||
4. | Archiving of biological and medical images: technical, ethical and legal aspects. |
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | Medical Image Processing, Reconstruction and Restoration | Jiri Jan | 0-8247-5849-8 | English |
Course | Mandatory/Advisable | Description |
SGN-1107 Introductory Signal Processing | Mandatory | |
SGN-1200 Signal Processing Methods | Advisable | |
SGN-1250 Signal Processing Applications | Advisable | |
SGN-2500 Introduction to Pattern Recognition | Advisable | |
SGN-2506 Introduction to Pattern Recognition | Advisable | |
SGN-3010 Digital Image Processing I | Mandatory | |
SGN-3016 Digital Image Processing I | Mandatory |
Course | Corresponds course | Description |
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Description | Methods of instruction | Implementation | |
Implementation 1 |