NDAK10005U Medical Image Analysis (MIA)

Volume 2015/2016
Education

MSc programme in Computer Science

MSc programme in Physics

Content

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. 

The course is aimed at students with interest in mathematics and computer science as well as the application of these to medical image analysis and related technologies.

The course is primarily aimed at students from computer science, physics and mathematics.

 

 

Learning Outcome

Knowledge:

After the course the studnt will have knowledge of:

  • Physics of X-ray formation
  • Computed tomography
  • Magnetic Resonance Imaging
  • Functional MRI
  • Positron Emission Tomography
  • Single Photon Emission Tomography
  • Medical statistics
  • Segmentation/Pixel classification
  • Shape modelling
  • Rigid & Non-rigid registration + Multi-modal registration
  • Shape statistics
  • Applications in Lung diseases
  • Application in cardiovascular diseases
  • Applications in joint diseases
  • Applications in neurology

 

Skills:

  • 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.
  • Understand the fundamental challenges in medical image analysis
  • Understand the representation of images in a computer
  • Read, understand and implement methods described in the scientific litterature in the field of medical imaging.
  • Apply implemented methods to medical images with the purpose of analyzing a specific pathology.


Competences.

  • The student will by the end of the course have ability to analyse, create and use pipelines of methods for the purpose of analyzing medical images in a scientific context

 

See Absalon when the course is set up.

The students are expected to have a mature and operational mathematical knowledge. Linear algebra, geometry, basic mathematical analysis, and basic statistics are mandatory disciplines.
Lectures, exersises, and assignments
  • Category
  • Hours
  • Class Instruction
  • 206
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Continuous assessment
Continuous assessment (4-6 written homework assignments).
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Re-exam

Oral exam (25 minutes without preparation).

Criteria for exam assesment

See learning outcome.