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.
- 20th February - Introductory Lecture (M. Stampanoni)
- Lecture Slides
- 27th February - Image Enhancement (A. Kaestner, held in HG E26.3!)
- Lecture Slides
- 6th March - Basic Segmentation, Discrete Binary Structures
- Lecture Slides
- Lecture Handout as PDF
- 13th March - Advanced Segmentation
- Lecture Slides
- Lecture Handout as PDF
- 20th March - Analyzing Single Objects
- Lecture Slides
- Lecture Handout as PDF
- 27th March - Analyzing Complex Objects
- Lecture Slides
- Lecture Handout as PDF
- 3rd April - Spatial Distribution
- Lecture Slides
- Lecture Handout as PDF
- 10th April - Statistics and Reproducibility
- Lecture Slides
- Lecture Handout as PDF
- 17th April - Dynamic Experiments
- Lecture Slides
- Lecture Handout as PDF
- 8th May - Scaling Up / Big Data
- Lecture Slides
- Lecture Handout
- 15th May - Guest Lecture - Applications in Material Science
- 22th May - Project Presentations
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.
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
- 20th February - Introductory Lecture (M. Stampanoni)
- Exercises 1
- Exercise Slides
- Starting Matlab Script
- 27th February - Image Enhancement (A. Kaestner, held in HG E26.3!)
- Exercises
- Starting Matlab Directory
- 6th March - Basic Segmentation, Discrete Binary Structures
- Exercise Slides
- Starting Matlab Script
- Data Files
- 13th March - Advanced Segmentation and Processing
- Lecture Quiz
- Exercise Slides
- Matlab Image Generator
- 20th March - Analyzing Single Objects
- Exercise Slides
- Matlab Image Generator
- 27th March - Analyzing Complex Objects
- Exercise Slides
- 3rd April - Spatial Distribution
- Exercise Slides
- Exercise Data
- Paraview Code
- 10th April - Statistics and Reproducibility
- Exercise Slides
- 17th April - Dynamic Experiments
- Exercise Slides
- Test Images
- 8th May - Big Data
- Exercise Slides
- Spark Data
- 15th May - Guest Lecture - Applications in Material Science
- Exercise Slides
- 22th May - Project Presentations
- Provide anonymous feedback on course here
- Or send direct email (slightly less anonymous feedback) to Kevin
- 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)
- Main Page
- Performance Computing Courses
- High Performance Computing for Science and Engineering (HPCSE) I
- Introduction to GPU Programming
- Programming Massively Parallel Processors with CUDA
- Reprodudible Research Courses
- Course and Tools in R
- Coursera Course