Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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Mathematical analysis
2° Year activated in the A.Y. 2022/2023
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1 module among the following3° Year activated in the A.Y. 2023/2024
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1 module among the following| Modules | Credits | TAF | SSD |
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Mathematical analysis
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1 module among the following| Modules | Credits | TAF | SSD |
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1 module among the following| Modules | Credits | TAF | SSD |
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Signal and image processing II (2023/2024)
Teaching code
4S008226
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Courses Single
Authorized
The teaching is organized as follows:
Teoria
Laboratorio
Learning objectives
The aim of the course is to provide students with the fundamental concepts and tools in order to apply advanced signal and image processing techniques in clinical studies based on imaging. The students will learn how to employ the most suitable algorithms and software tools to be able to solve the most typical problems that may arise in imaging studies.
Prerequisites and basic notions
Attendance of the "Signals and images 1" course is recommended but not strictly necessary for a correct and proper understanding of the course.
Program
THEORY
- Recalls of fundamental concepts of biomedical signals / images
- Methods for improving the quality and restoration of images (e.g. HDR imaging, Wiener)
- Extraction of features (e.g. Canny, Hough)
- Extraction of regions (e.g. Watershed, region growing, snakes)
- Morphological operators
- Image registration / alignment
- Image compression algorithms
LABORATORY
During the laboratory sessions some of the methodologies covered during the theory lectures will be studied more in depth by solving signal / image processing problems mainly using PYTHON.
Didactic methods
Classical lectures for the theory part, while in the hands-on sessions the students will have the opportunity to experiment and deepen the topics seen in theory through the use of PYTHON.
Learning assessment procedures
The exam consists of a written test with open-ended questions and exercises on the topics covered in the course.
Evaluation criteria
Typically the exam includes 8 questions (one on each of the macro-topics covered in the course), and each question can have a grade between 0 and 4. The final grade is expressed out of thirty (32 = 30L).
Criteria for the composition of the final grade
The exam does not include a laboratory test.
Exam language
Italiano
