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Course module: BMB502517
BMB502517
Capita Selecta in Medical Imaging
Course info
Course codeBMB502517
EC5
Course goals
After completing the course the student:
  • will be familiar with the concepts of machine learning and deep learning
  • will be familiar with the latest developments and clinical applications of these techniques
  • has a basic understanding of neural networks for medical image analysis
  • can identify common MRI artifacts present in diffusion MRI data
  • will know the basic processing steps that are required for diffusion MRI
  • is able to discriminate between different diffusion MRI model strategies
  • will have a basic hands-on knowledge of analysing and visualizing diffusion MRI data
  • will understand the limitations and pitfalls in the context of neuroscientific and biomedical applications
Content
Period (from – till): 9 November 2020 - 1 February 2021
 
Course coordinator: Dr. Alexander Leemans
 
Faculty
Dr. Alexander Leemans, UMC Utrecht/Imaging & Oncology Division, lecturer
Dr. Hugo Kuijf, UMC Utrecht/Imaging Imaging & Oncology, lecturer
Renée Allebrandi, MA (course registration)
 
Course description:
This course consists of two independent topics. During the first half of the course , topics on deep learning for medical image analysis will be introduced: :
  • Machine Learning fundamentals
  • Deep Learning
  • Convolutional Neural Network
  • Network Architectures
  • Medical Image Analysis applications
 
During practical sessions students will improve their understanding of the above topics. Additionally there will be a homework group assignment to be handed in at the end of the course.
 
The second half of the course covers theory and practice of processing, analysing and visualising diffusion MRI data. Key concepts and practical considerations of data processing and analysis are explained. Topics include
  • Quality assessment
  • Artifact correction
  • Diffusion approaches
  • Fiber tractography
  • Automated analyses
  • Visualisation methods
During computer practical sessions students will learn how to work with real diffusion MRI data.
 
Literature/study material used:
Deep Learning, by Goodfellow, Bengio, Courville, https://www.deeplearningbook.org/
hand-outs provided by lecturers
suggested reading material
 
Details: https://mix.isi.uu.nl/courses/capita-selecta-medical-imaging-uu/
 
Registration
You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.
Students from outside the UU or TU/E partnership can register for this course by sending an email to mix@isi.uu.nl. Please include your name, student number, Master’s programme and the course code.
 
Mandatory 
No.

Optional for students in other GSLS Master’s programme:
Yes.
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