|
| Udgave: |
Efterår 2012 NAT |
| Point: |
7,5 |
| Blokstruktur: |
2. blok |
| Skemagruppe: |
B |
| Fagområde: |
dat |
| Varighed: |
8 weeks |
| Institutter: |
Department of Computer Science |
| Uddannelsesdel: |
Kandidat niveau |
| Kontaktpersoner: |
Mads Nielsen; Phone: 3532 1450; E-mail: madsn@diku.dk |
| Skema- oplysninger: |
 Vis skema for kurset
Samlet oversigt over tid og sted for alle kurser inden for Lektionsplan for Det Naturvidenskabelige Fakultet Efterår 2012 NAT |
| Undervisnings- form: |
Lectures, exersises, and assignments |
| Formål: |
Medical diagnosis, prognosis and quantification of progression is in general based on biomarkers. These may be blood or urin markers, but currently imaging is taking over as more indicative for many purposes.
This course will give an introduction to medical image formation in the different scanning modalities: X-ray, CT, MR, fMRI, PET, US etc. We will continue with the underlying image analysis disciplines of detection, registration, and segmentation, and end with specific applications in clinical practise. A key to achieve success in the application is formal evaluation of methodologies why performance characterisation also is a central topic.
We will use techniques from image analysis and real world examples from the clinic.
The course is aimed at providing sufficient background knowledge for doing master theses (specialer) as well as student projects.
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| Indhold: |
The course will cover essential aspects of medical image analysis. Among the topics are:
Physics of X-ray formation
Computed tomography
Magnetic Resonance Imaging
Functional MRI
Positron Emission Tomography
Single Photon Emission Tomography
Medical statistics
Segmentation by Watersheds
Pixel classification
Shape modelling
Rigid registration
Non-rigid registration
Multi-model registration
Shape statistics
Applications in Lung diseases
Application in cardiovascular diseases
Applications in joint diseases
Applications in neurology
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| Målbeskrivelse: |
After completion of the course the student will be able to:
Explain how medical images are formed
Describe central algorithms for image segmentation and registration
Describe the central aspects of shape statistics
Describe the central paradigms of medical statistics
Design, implement, and apply methods from image analysis to the medical domain to obtain experimental insights.
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| Tilmelding: |
Via KUnet from May 15th to June 1st. |
| Faglige forudsætninger: |
The students are expected to have a mature and operational mathematical knowledge. Linear algebra, geometry, basic mathematical analysis, and basic statistics are mandatory disciplines. |
| Eksamensform: |
Exam: Continuous assessment (4-7 written homework assignments). Grades given according to the 7-step scale. Internal grading.
Re-exam: Oral exam (25 minutes without preparation). Internal grading and grades given according to the 7-step scale.
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| Eksamen: |
Løbende evaluering.
Reeksamen: Mundtlig prøve den 19. april 2013.
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| Kursus hjemmeside: |
 |
| Undervisnings- sprog: |
Kun engelsk
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| Sidst redigeret: |
25/4-2012 |