Fundamentals of Image Analysis
EE-805 / 2 credits
Teacher(s): Andò Edward Carlo Giorgio, Sage Daniel, Unser Michaël
Language: English
Remark: 24-28 June 2024 - Information: https://imaging.epfl.ch/summer-school - Registrations: https://forms.gle/FNrdTrBwW7xExt9y9 - Application deadline: 17 March 2024
Frequency
Every year
Summary
This summer school is an hands-on introduction on the fundamentals of image analysis for scientists. A series of lectures provide students with the key concepts in the field, and are followed by practical sessions with popular software on the participants' own image-analysis software.
Content
The summer school is structured around 7 sessions, each covering a specific imaging topic (see below). There will be one to two sessions per day, each consisting of lectures and interactive practical works on the current thematic:
Fundamentals of Scientific Images
Key concepts in digital imaging (pixel level, contrast, histogram, file format, etc.), multidimensional data (visualisation)
Image Acquisition
Optics of image formation (light sources, PSF/MTF, etc.), noise, SNR, resolution, 3D scenes, stereo imaging
Operations on Digital Images
Digital filters, morphological operators, segmentation
Motion Tracking
Optical flow and registration, measuring a displacement field (local, global, discrete), representing and quantifying deformations, tracking of particles (detection and linking)
Machine Learning for Image Analysis
Key terminology, data preparation, existing ML software for image analysis
Deep Learning for Image Analysis
Building and training of models, running of pre-trained models, fine-tuning of pre-trained models
Good Practice for Open Imaging
Ethics of image publication, the do's and don't of figure preparation, storage, formats, licenses, open access, confidentiality
Note
This course is a transversal initiative from the EPFL Center for Imaging.
More information, as well as the schedule are available in this link https://imaging.epfl.ch/summer-school
Keywords
Image analysis, digital images, image acquisition, deep learning, open imagine.
Assessment methods
Written exam.
In the programs
- Number of places: 25
- Exam form: Written (session free)
- Subject examined: Fundamentals of Image Analysis
- Lecture: 22 Hour(s)
- Exercises: 9 Hour(s)
- Practical work: 10 Hour(s)
- Type: optional
- Number of places: 25
- Exam form: Written (session free)
- Subject examined: Fundamentals of Image Analysis
- Lecture: 22 Hour(s)
- Exercises: 9 Hour(s)
- Practical work: 10 Hour(s)
- Type: optional