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

Reference week

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