Level of education
Master's degree
ECTS
4 credits
Training structure
Faculty of Science
Hours per week
24h
Description
This course provides an introduction to scientific image processing, with no prerequisites, in the context of physics and medical sciences.
Starting with the basics of digital image coding, we will introduce the main techniques aimed first at improving image data quality, then at extracting quantitative data. Deconvolution, denoising, thresholding, segmentation, Fourier transforms, and wavelets will be covered.
We will conclude with the specific problems posed by image sequences (films) or 3D images such as MRI data in a medical context.
The tool used will be the Matlab/Octave programming environment.
Objectives
This course aims to provide students with a basic understanding of image processing and analysis, enabling them to independently tackle the specialized problems they will encounter in various experimental contexts.
Mandatory prerequisites
Recommended prerequisites:
Matlab/Octave programming.
Knowledge assessment
Final exam on the machine
Syllabus
- Introduction to OCTAVE/MATLAB
- Fundamental image processing tools
- Deconvolution, noise reduction, pre-processing
- Fourier and Wavelets
- Advanced segmentation
- Correlations, realignment, 3D data
- MRI and spatial statistics tools