Lecture: Image Acquisition and Analysis in Neuroscience
- Start: Mon. 24.10.2015, 10:30 am, LBH I.80
- Dates: Mon. and Thu. 10:15 - 11:45, LBH I.80
- Course number: MA-INF 2312
- Curriculum: Master
- Effort: 4.0 SWS / 6 CP
Lectures have been moved to 10:15-11:45 according to student demand.
Please subscribe to our mailing list to receive important information concerning the lecture and exercises!
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 recognize 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
- 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.
The lecture takes place twice a week - Monday and Thursday - with an exercise class replacing the lecture roughly every other week. The specific exercise dates are: Mon Nov 7, Mon Nov 21, Thu Dec 1, Thu Dec 15, Thu Jan 12, Thu Feb 2. There will be individual oral exams at the end of the semester.
- Introduction (PDF document, 2.4 MB)
- Fourier-and-Signal-Processing (PDF document, 1.6 MB)
- Magnetic-Resonance-Imaging (PDF document, 2.5 MB)
- Registration-Normalization (PDF document, 2.0 MB)
- Segmentation (PDF document, 2.2 MB)
- Statistical-Testing (PDF document, 1.7 MB)
- Functional-MRI (PDF document, 3.2 MB)
- Diffusion-MRI (PDF document, 3.5 MB)
- Machine-Learning (PDF document, 2.9 MB)
Exercise 1: Fourier-Analysis
Assignment sheet (PDF document, 170 KB)
Exercise 2: Magnetic-Resonance-Imaging
Assignment sheet (PDF document, 237 KB)
Exercise 3: Registration
Assignment sheet (PDF document, 200 KB)
Exercise 4: Segmentation
Assignment sheet (PDF document, 218 KB)
Exercise 5: Statistics
Assignment sheet (PDF document, 164 KB)
Exercise 6: fMRI-and-dMRI
Assignment sheet (PDF document, 190 KB)
- foundations-of-scientific-visualization (PDF document, 1.1 MB)