Introduction to Medical Image Analysis, Short Course | Part time online | KTH Royal Institute of Technology | Sweden
Studyportals
Short Online

Introduction to Medical Image Analysis

2 months
Duration
Unknown
Tuition fee
Unknown
Unknown
Apply date
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Start date

About

The Introduction to Medical Image Analysis course offered by KTH Royal Institute of Technology aims to study the most used methods in 3D image analysis (extract relevant information from images) and their use in medical applications.

Overview

What you will study

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

After completing the course, the participant should be able to:
  • Understand the main problems and challenges in image analysis
  • 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 analysis in a medical context
  • be able to implement computational solutions in image analysis to medically relevant problems
  • have a broad knowledge base that can facilitate understanding literature in the field

Programme Structure

The program focuses on:

  • Feature extraction
  • Image classification
  • Image regression
  • Machine learning and deep learning for image analysis

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, scikit-learn, TensorFlow, etc. The course also includes introductory labs for students with programming experience but no Python experience.

Key information

Duration

  • Part-time
    • 2 months

Start dates & application deadlines

Language

English
TOEFL admission requirements TOEFL® IBT
90

Credits

2 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

Funding

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Introduction to Medical Image Analysis
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Introduction to Medical Image Analysis
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