NDAK10005U Medical Image Analysis

Volume 2014/2015
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. 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

 

Learning Outcome

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.

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 (4-7 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.