NDAK10005U Medical Image Analysis
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.
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
Knowledge:
Basic understanding of Medical image acquisition techniques such CT
MRI and PET
Insight to the field of medical image analysis in relation to
pathologies and clinical investigations
The fundamental challenges in medical image analysis
understand the representation of image sin a computer
skills
Be able implement simple medical image processing algorithms e.g.
image registration or segmentation.
Implements pipelines of processing of medical images
Evaluate the quality of a given result
Apply image processing to medical images with the purpose of
analyzing a specific pathology
Competences.
The student will have insight into the foundation medical images
analysis and is able to evaluate if medical image analysis
techniques are applicable to a specific problem. The students will
have a basic understanding of the legislative requirements for
commercializing a medical image processing device/software
product.
See Absalon when the course is set up.
- Category
- Hours
- Class Instruction
- 206
- Total
- 206
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
- Credit
- 7,5 ECTS
- Type of assessment
- Continuous assessmentContinuous assessment (4-7 written homework assignments).
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal censor.
- Re-exam
- Oral exam (25 minutes without preparation).
Criteria for exam assesment
See learning outcome.
Course information
- Language
- English
- Course code
- NDAK10005U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- B (Mon 8-12 + Tues 13-17 + Fri 8-12)
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Course responsibles
- Sune Darkner (7-6a677871746b78466a6f34717b346a71)