Medical Image Analysis

Higher education teachers: Špiclin Žiga
Credits: 6
Semester: winter
Subject code: 64279



Subject description

Prerequisits:

  • Enrolment into the 2nd year of the Master’sstudy programme ofElectrical Engineering

Content (Syllabus outline):

Introduction: medical image analysis in clinical practice

Segmentation and quantitative analysis: classification and applicability of methods, thresholding, edge- and region-based techniques, model- and atlas-based methods, supervised and unsupervised methods, cluster-based, principal component analysis, statistical shape and appearance models

Computer-aided diagnosis: feature selection and extraction, decision functions, distance measures in cluster analysis, statistical classification, fuzzy classification, neural networks, receiver operating characteristics (ROC), successful applications.

Image-guided medical procedures: intrinsic and extrinsic information-based tracking and navigation, procedure planning and visualization, registration of pre- and intra-interventional data, validation of registration methods, applications of image-guided procedures.

Objectives and competences:

The objective of this course is to provide students with an overview of the computational and mathematical methods in medical image processing and analysis. Several up-to-date automated methods aimed to enhance and extract useful information from medical images, such as X-ray, CT, MRI, PET, will be presented. A variety of diagnostic and interventional scenarios will be used as examples to motivate the methods.

Intended learning outcomes:

The students will learn how to extract, model, and analyse information from medical images and apply this information in order to help/enhance diagnosis, treatment and monitoring of diseases through engineering techniques.

Learning and teaching methods:

Lectures, lab works and individual assignements.





Study materials

  1. Wolfgang Birkfellner. Applied Medical Image Processing, Second Edition: A Basic Course. CRC Press; 2 edition, 2014.
  2. Isaac Bankman. Handbook of Medical Image Processing and Analysis, Second Edition (Academic Press Series in Biomedical Engineering), Academic Press; 2 edition, 2008.
  3. Michael Fitzpatrick and Milan Sonka. Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis (Parts 1 and 2) (SPIE Press Monograph Vol. PM80/SC), SPIE Publications; Reprint edition, 2009.
  4. Terry Peters, Kevin Cleary. Image-Guided Interventions: Technology and Applications, Springer, 1st edition, 2008.



Study in which the course is carried out

  • 2 year - 2nd cycle - Electrical Engineering - Biomedical Engineering