Quantitative Big Imaging Course
Here are the lectures, exercises, and additional course materials corresponding to the spring semester 2014 course at ETH Zurich, 227-0966-00L: Quantitative Big Imaging. The lectures have been prepared and given by Kevin Mader, Anders Kaestner, Marco Stampanoni, and Maria Büchner. Please note the Lecture Slides and PDF do not contain source code, this is only available in the handout.
Lectures
- 20th February - Introductory Lecture (M. Stampanoni)
- 27th February - Image Enhancement (A. Kaestner, held in HG E26.3!)
- 6th March - Basic Segmentation, Discrete Binary Structures
- 13th March - Advanced Segmentation
- 20th March - Analyzing Single Objects
- 27th March - Analyzing Complex Objects
- 3rd April - Spatial Distribution
- 10th April - Statistics and Reproducibility
- 17th April - Dynamic Experiments
- 8th May - Scaling Up / Big Data
- 15th May - Guest Lecture - Applications in Material Science
- 22th May - Project Presentations
Final Examination
The final examination (as originally stated in the course material) will be a 30 minute oral exam covering the material of the course and its applications to real systems. For students who present a project, they will have the option to use their project for some of the real systems related questions (provided they have sent their slides to Kevin after the presentation and bring a printed out copy to the exam including several image slices if not already in the slides). The exam will cover all the lecture material from Image Enhancement to Scaling Up (the guest lecture will not be covered). Several example questions (not exhaustive) have been collected which might be helpful for preparation.
Exercises
General Information
The exercises are based on the lectures and take place in the same room after the lecture completes.
- For the first 3 exercises, QBI Install is required for starting the exercises and contains Fiji along with a few test datasets.
- For the subsequent exercies, the script can be run inside Matlab
Specific Assignements
- 20th February - Introductory Lecture (M. Stampanoni)
- 27th February - Image Enhancement (A. Kaestner, held in HG E26.3!)
- 6th March - Basic Segmentation, Discrete Binary Structures
- 13th March - Advanced Segmentation and Processing
- 20th March - Analyzing Single Objects
- 27th March - Analyzing Complex Objects
- 3rd April - Spatial Distribution
- 10th April - Statistics and Reproducibility
- 17th April - Dynamic Experiments
- 8th May - Big Data
- 15th May - Guest Lecture - Applications in Material Science
- 22th May - Project Presentations
Feedback
- Provide anonymous feedback on course here
- Or send direct email (slightly less anonymous feedback) to Kevin
Other Material
- Project Signup
- Here you signup for your project with team members and a short title and description
- List
- Course Wiki (For Questions and Answers, discussions etc)
- Performance Computing Courses
- Reprodudible Research Courses