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Overview
What you will learn
On successful completion of the Deep Learning Methods for Medical Image Analysis course offered by KTH Royal Institute of Technology, the student should be able to:
- explain the basic principle of supervised deep learning methods for medical image segmentation and classification
- account for the theoretical background for the methods for deep neural networks used in the context of medical image analysis
- explain the commonly used deep neural network architectures and their functions in medical image analysis
- identify the practical applications in the field of medical image analysis where deep learning can be applied
in order to:
- be able to prepare medical images for deep learning based methods
- be able to implement, analyze and evaluate common deep neural networks for medical image analysis
- use the basic knowledge acquired during the course to learn more about the area and read literature in the area
Programme Structure
The program focuses on:
- Ssupervised learning and its applications in medical image analysis
- Basic theories of ANN and DNN: Active function, Loss function, gradient descent, layers
- The principle of convolutional neural networks (CNN) and recurrent neural networks (RNN)
- Python and TensorFlow
- Medical image segmentation using CNN and hands-on section with TensorFlow
- Medical image classification using CNN and hands-on section with TensorFlow
- Medical image analysis using RNN and hands-on section with TensorFlow
- Transferred learning and deep features for medical image analysis
- New progress in methods for deep learning
Key information
Duration
- Full-time
- 2 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
English
TOEFL® IBT 90
Credits
7 ECTS
Delivered
On Campus
Disciplines
Artificial Intelligence Machine Learning Medical Imaging View 4 other Short Courses in Machine Learning in SwedenAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
TOEFL® IBT 90
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
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Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at KTH Royal Institute of Technology and/or in Sweden, please visit Student Insurance Portal.
Other requirements
General requirements
- Bachelor’s degree in Engineering Physics, Electrical Engineering, Computer Science or equivalent.
- 6 credits programming.
- English B/6
Tuition Fee
To always see correct tuition fees
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EU/EEA
FreeTuition FeeBased on the tuition of 0 SEK for the full programme during 2 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.
Living costs for Stockholm
9668 - 17248 SEK /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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