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
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026The 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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2° Year activated in the A.Y. 2014/2015
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Tre insegnamenti a scelta tra i seguenti
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.
Image and volume data analysis (2014/2015)
Teaching code
4S001409
Teacher
Coordinator
Credits
6
Also offered in courses:
- Bioimaging and Biomedical data processing - ELABORAZIONE DATI BIOMEDICI of the course Master's degree in Bioinformatics and Medical Biotechnology
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
I sem. dal Oct 1, 2014 al Jan 30, 2015.
Learning outcomes
The course presents different algorithmic tools that can be used to analyse spatially referenced data as images voxelized volumes, captured surfaces in order to perform measurements, recognize objects and derive semantic interpretation of the acquired scene.
Different examples of data will be presented, as well as potential applications and several tools for recovering object location and shapes, aligning different data, visualize spatial information and analysing properties of detected objects will be presented.
Program
Images and volumetric data: acquisition devices, applications in different contexts
Visualization of 3D data
Image and volume segmentation: methods based on classifiers, spatial priors, graphs. Interactive segmentation
Contour/surface based segmentation
Model based segmentation
Image and contour/surface registration, methods based on feature matching and methods based on volume comparison
Shape analysis: algorithms and descriptors
Texture analysis: algorithms and descriptors
Applications
Examination Methods
Written essay (20/30) and evaluation of programming project (10/30)