Deep Learning with Applications in Medical Imaging
Spring Term 2024
About the course
This course covers deep convolutional neural networks (CNNs) for computer vision, with applications in medical image analysis. The course provides an introduction to fundamental concepts in machine learning, describes neural networks and the field of deep learning, and goes into detail about deep CNNs. The course describes the different parts that are used when building deep CNNs, such as filters, activation functions, loss functions; regularization techniques such as e.g. batch normalization and dropout; explains several of the different non-linear optimization algorithms that are used when training the networks, such as stochastic gradient descent, Adam, etc.; and describes popular network architectures, such as e.g. the U-Net, ResNet, and DenseNet, and discusses their pros and cons. The course also covers generative models, such as variational autoencoders (VAE) and generative adversarial networks (GANs).
Students in this course will learn to implement and train modern network architectures and deep learning methods, and apply these to large image datasets with medical and other images.
Deep Learning with Applications in Medical Imaging, 7.5 credits
Spring Term 2024
15 January 2024
2 June 2024
English (upon request)
Type of studies
Univ: For access to the course requires 90 credits of completed studies in one of the main areas of computer science, physics, electronics, chemistry, mathematics or mathematical statistics are required, or 2 years of completed studies (120 credits). Of these credits, at least 7.5 credits are required in basic programming methodology in Python, C, and/or Matlab, at least 7.5 credits dealing with Data Structures and Algorithms, at least 7.5 credits dealing with Linear Algebra, at least 7.5 credits dealing with analysis with concepts such as derivatives and limit values, at least 7.5 credits dealing with mathematical statistics, or equivalent knowledge. English A/6 if the teacing language is english.
Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.
Please note: This application round is intended only for applicants within the EU/EEA and Switzerland.
Online application service in Swedish will open 15 September 2023 at 13:00 CET.
Application deadline is
16 October 2023. How to apply
Application and tuition fees
As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.