Lecture: Image Acquisition and Analysis in Neuroscience

Course

  • Lecturer(s):
  • Start: Mon. 11.10.2021, 14:15
  • Dates: Mon. and Thu. 14:15-15:45
  • Course number: MA-INF 2312
  • Curriculum: Master , B-IT Master Media Informatics
  • Effort: 4.0 SWS / 6 CP
  • Exams: TBA

Exercises

  • Tutor(s):
  • Start: Mon. 04.11.2021 14:15 - 15:45
  • Dates: Nov 4, Nov 15, Nov 29, Dec 13, Jan 13, Jan 24

Description

This year, the lecture will be organized via the eCampus platform. Please sign up there to receive all relevant information.

Magnetic Resonance Imaging (MRI) along with its modern variants functional and diffusion MRI have become indispensable tools in neuroscience: Imaging the living brain allows us to detect brain regions that engage in specific tasks, to investigate the wiring of the brain, to study and to quantify the effects of aging or disease. Recently, some image-based studies have even made the headlines, suggesting that MR imaging might be used to detect lies, diagnose psychiatric disease, or identify images viewed by the subject in the scanner.

This lecture will make you understand the wide range of image processing and pattern recognition methods behind such results. In particular, image acquisition and analysis in neuroscience require the following computational methods:

  • Image reconstruction for Magnetic Resonance Imaging
  • 3D Image Registration
  • 3D Image Segmentation
  • Models for functional MRI (fMRI) and diffusion MRI (dMRI) data
  • Statistical Hypothesis Testing
  • Applications of Machine Learning

The lecture conveys an understanding of all these topics, and is ideally suited to prepare you for a lab course or a master thesis in this field. At the same time, you will learn about some fundamental methods in medical image processing, statistical modeling, and machine learning, which are useful far beyond their applications in neuroimaging.

Organization

The lecture takes place twice a week - Monday and Thursday - with an exercise class replacing the lecture roughly every other week.