Medical Image Segmentation, Short Course | Part time online | KTH Royal Institute of Technology | Sweden
3 months
Duration
Free
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

The Medical Image Segmentation course offered by KTH Royal Institute of Technology aims to study the most used methods in 3D image segmentation (extract relevant areas) and their use in medical applications.

Overview

What you will study

The Medical Image Segmentation course offered by KTH Royal Institute of Technology covers concepts, theories, and the most used methods in image segmentation. The course is focused on solving medically relevant problems.

After completing the course, the participant should be able to:
  • Understand the key issues and challenges in image segmentation
  • Describe the main principles and methods and the main differences between them
  • Summarize the advantages and disadvantages and scope of different methods
  • Identify and understand the mathematical theory behind the most used methods
  • Develop and systematically evaluate different methods for solving simplified problems
  • Analyze the effect of different parameters of the methods in particular situations
  • Explain the proposed strategy for solving specific problems
in order to:
  • understand the complete workflow for using computational tools for image segmentation in a medical context
  • be able to implement computational solutions in image segmentation for medically relevant problems
  • have a broad knowledge base that can facilitate understanding literature in the field

Programme Structure

The program focuses on:

  • Voxel-based image segmentation
  • Graph-based image segmentation
  • Contour-based image segmentation
  • Model-based image segmentation
  • Image segmentation with deep learning
The course consists of lectures, laboratories, mathematical exercises, and an exam. Participants combine basic and advanced software libraries for image registration in Python, including scipy, numpy, SimpleITK, scikit-image, etc. Some specific labs use MATLAB and Mialab, an image segmentation tool developed at KTH. The course also includes introductory labs for students with programming experience but no Python experience.

Key information

Duration

  • Part-time
    • 3 months

Start dates & application deadlines

Language

English
TOEFL admission requirements TOEFL® IBT
90

Credits

3 ECTS

Delivered

Online

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

TOEFL admission requirements TOEFL® IBT
90

Other requirements

General requirements

  • Bachelor's degree in Medical Technology, Engineering Physics, Electrical Engineering, Computer Science or equivalent. 
  • At least 6 credits in programming. 
  • English B/English 6.

Tuition Fee

To always see correct tuition fees
  • EU/EEA

    Free
    Tuition Fee
    Based on the tuition of 0 SEK for the full programme during 3 months.

If you are an EU, EEA or Swiss citizen or hold a residence permit in Sweden for something other than studies you generally do not have to pay tuition fees.

Funding

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Our partners

Medical Image Segmentation
KTH Royal Institute of Technology
Medical Image Segmentation
-
KTH Royal Institute of Technology

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