Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
The aim of this course is to provide the basic knowledge of methods and models for biomedical signal and image processing, developing the ability to analyze and solve problems of interest, mainly in the biomedical field. Each technique presented will be accompanied by applications on simulated and real signals. At the end of the course, the student will be able to show knowledge of the main methods of biomedical signals and image processing. They will possess the ability to formulate, ana- lyze and solve problems of interest in bioengineering, through the acquired theoretical and practical basic knowledge. Finally, the student will be able to evaluate the traditional methods in the biomedical sciences in order to devise new approaches to methodological problems with clinical reversibility.
Prerequisites and basic notions
Mathematical analysis (series, sequences, derivatives, integrals) Probability and statistical calculations (random variables, known - Gaussian and exponential distributions)
- Introduction to the signal and image processing
- Preliminary mathematics
- Signals and their taxonomy
- Fourier analysis, 1D and 2D
- Methods for improving image quality (image enhancement) in both the spatial and frequency domains
- Extraction of image contours
- Extraction of image regions
- Morphological operators
- Representation and processing of color images
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“The teacher / teachers will use: a) frontal lessons; b) laboratory sessions (MATLAB) c) exercises on the blackboard All these will be recorded to be used also at a later time. Mixed mode (zoom) will NOT be present
Learning assessment procedures
Written exam, lasting 2 hours. The test consists in solving analytical exercises, in producing answers to open questions, and, as regards the laboratory part, in writing MATLAB code to solve a specific problem. It is therefore not necessary to do any separate laboratory tests. Exam methods are NOT differentiated between attending and non-attending students and for Erasmus students. The course does NOT include intermediate tests.
Ability to identify an effective and theoretically correct technical solution to a signal and image processing problem. Ability to discursively organize knowledge; critical reasoning skills on the study carried out; quality of exposure, competence in the use of specialized vocabulary. The evaluation is expressed out of thirty.
Criteria for the composition of the final grade
24 points max for the theory part, 6 points max for the laboratory part. Honors are at the discretion of the teacher, and necessarily requires that in both modules (theory and laboratory) the maximum scores have been obtained