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
- StartingApplication deadline not specified.
Language
Credits
Delivered
Disciplines
Artificial Intelligence Machine Learning Medical Imaging View 12 other Short Courses in Artificial Intelligence in SwedenWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Student insurance
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- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
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Other requirements
General requirements
- Bachelor’s degree in Engineering Physics, Electrical Engineering, Computer Science or equivalent.
- 6 credits programming.
- English B/6
Tuition Fee
Living costs for Stockholm
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.