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.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
Primo semestre Oct 4, 2021 Jan 28, 2022
Secondo semestre Mar 7, 2022 Jun 10, 2022
Exam sessions
Session From To
Sessione invernale d'esame Jan 31, 2022 Mar 4, 2022
Sessione estiva d'esame Jun 13, 2022 Jul 29, 2022
Sessione autunnale d'esame Sep 1, 2022 Sep 30, 2022
Degree sessions
Session From To
Sessione Estiva Jul 15, 2022 Jul 15, 2022
Sessione Autunnale Oct 14, 2022 Oct 14, 2022
Sessione Invernale Mar 14, 2023 Mar 14, 2023
Holidays
Period From To
Festa di Tutti i Santi Nov 1, 2021 Nov 1, 2021
Festa dell'Immacolata Concezione Dec 8, 2021 Dec 8, 2021
Festività natalizie Dec 24, 2021 Jan 2, 2022
Festa dell'Epifania Jan 6, 2022 Jan 7, 2022
Festività pasquali Apr 15, 2022 Apr 19, 2022
Festa della Liberazione Apr 25, 2022 Apr 25, 2022
Festività Santo Patrono di Verona May 21, 2022 May 21, 2022
Festa della Repubblica Jun 2, 2022 Jun 2, 2022
Chiusura estiva Aug 15, 2022 Aug 20, 2022

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

A B C D F G L M P S

Accordini Simone

simone.accordini@univr.it +39 045 8027657

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bombieri Cristina

cristina.bombieri@univr.it 045-8027284

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Constantin Gabriela

gabriela.constantin@univr.it 045-8027102

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Franco Giuditta

giuditta.franco@univr.it +39 045 802 7045

Giugno Rosalba

rosalba.giugno@univr.it 0458027066

Laudanna Carlo

carlo.laudanna@univr.it 045-8027689

Liptak Zsuzsanna

zsuzsanna.liptak@univr.it +39 045 802 7032

Malerba Giovanni

giovanni.malerba@univr.it 045/8027685

Marcon Alessandro

alessandro.marcon@univr.it +39 045 802 7668

Marzola Pasquina

pasquina.marzola@univr.it 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Molesini Barbara

barbara.molesini@univr.it 045 802 7550

Perduca Massimiliano

massimiliano.perduca@univr.it +39 045 802 7984

Sala Pietro

pietro.sala@univr.it 0458027850

Salvagno Gian Luca

gianluca.salvagno@univr.it 045 8124308-0456449264

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 enrolment year.

ModulesCreditsTAFSSD
Further linguistic skills (C1 English suggested)
3
F
-
Stages
3
F
-
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°

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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S004554

Credits

6

Coordinatore

Alessandro Daducci

Language

English en

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

The teaching is organized as follows:

Teoria

Credits

4

Period

Secondo semestre

Academic staff

Alessandro Daducci

Laboratorio

Credits

2

Period

Secondo semestre

Academic staff

Alessandro Daducci

Learning objectives

The course aims at providing students with the applied and theoretical basis for processing biomedical images and extract useful information from them to support the diagnosis process. Knowledge and understanding. At the end of the course, the student shall demonstrate that he/she can apply the material discussed in the lectures to solve effectively the most common issues that may happen throughout a typical analysis pipeline, from the acquisition of the raw images to the correct interpretation of the information extracted from them. Applying knowledge and understanding. In particular, at the end of the course the student shall demonstrate to be able to: a) open, handle and manipulate the multidimensional data acquired with the major imaging modalities (X-rays, magnetic resonance imaging, nuclear medicine and ultrasounds); b) evaluate advantages, disadvantages and peculiarities of each modality; c) interpret correctly the content of such images and be able to link them to physical and biological features of the tissue/organ under exam. Making judgements. The student will be able to develop an analysis pipeline to extract useful information from such biomedical images and help the diagnostic process, applying at each step the most adequate processing choices for the specific data at hand. Communication. At the end of the course, the student shall demonstrate the ability to effectively interact with different collaborators having specific backgrounds typically required in a clinical study based on medical imaging, e.g. engineers, physicists, physicians etc. Lifelong learning skills. He/she will also have the required foundations to be able to elaborate further on any scientific, methodological and recent advances in the field beyond the content of the lectures to extend such basic techniques to diverse and more complex analysis scenarios.

Prerequisites and basic notions

Good familiarity with the main contents of basic courses such as "Signal and image processing" is strongly recommended (but not strictly necessary) for a proper and complete understanding of the course.

Program

(1) Basic concepts
- Image properties: pixel vs voxel, spatial resolution, orientation, data type, etc
- File formats
- Signal-to-noise ratio, Contrast-to-noise ratio, etc

(2) Main imaging modalities (recall principles)
- Radiography: X-rays projection, fluoroscopy and computed tomography
- Nuclear medicine: SPECT and PET
- Ultrasounds
- Magnetic Resonance Imaging

(3) Medical image registration
- Geometric transformations
- Features and similarity measures
- Transformations (linear vs non-linear)

(4) Morphometry analysis
- Region-of-interest analysis
- Voxel-based morphometry
- Surface-based morphometry
- Tract-based morphometry in white matter

(5) Structural connectivity estimation
- Diffusion MRI: principles and main applications
- Estimating microstructural features of the neuronal tissue
- Inferring fibers geometry and organization (a.k.a. tractography)
- Recent advances

(6) Functional connectivity estimation
- Physiology of neurons and how to record their activity
- Functional MRI: principles and main applications
- Elettroencefalography and magnetoencefalography: principles and main applications
- Static vs dynamic connectivity

(7) Network analysis (a.k.a. connectomics)
- A network representation of the brain: how and why?
- Studying brain networks with graph theory: concepts and measures
- Comparing brain networks in different groups of subjects

(8) Laboratory
- Hands-on activities on the topics covered throughout the course
- Real neuroimaging data provided to be analyzed

Didactic methods

Lectures for the theory part with various invited talks given by international experts; in the laboratory part, students will install and use the main software to analyze real images of clinical studies. All lessons will be recorded and made available.

Learning assessment procedures

The exam consists of a project, assigned at the end of the course, aimed at analyzing magnetic resonance images taken from a real clinical study. This final project is a fundamental part of the course, as it provides students with the opportunity to put into practice the concepts studied during the theory part, understand the peculiarities of each acquisition mode, touch some typical problems that can occur when biomedical images are processed and the most appropriate techniques applied to improve the quality of the images and extract useful information from them.

Evaluation criteria

The evaluation will be based on (A) a short written report (max 10 pages) and (B) an oral presentation / discussion (which may also include questions on the theory part), in which both the exposure and the interpretation of the methodologies used and the results obtained will be assessed.

Criteria for the composition of the final grade

The final grade will consist of 50% of the written report and 50% based on the presentation.

Exam language

English

Type D and Type F activities

Le attività formative di tipologia D sono a scelta dello studente, quelle di tipologia F sono ulteriori conoscenze utili all’inserimento nel mondo del lavoro (tirocini, competenze trasversali, project works, ecc.). In base al Regolamento Didattico del Corso, alcune attività possono essere scelte e inserite autonomamente a libretto, altre devono essere approvate da apposita commissione per verificarne la coerenza con il piano di studio. Le attività formative di tipologia D o F possono essere ricoperte dalle seguenti attività.

1. Insegnamenti impartiti presso l'Università di Verona

Comprendono gli insegnamenti sotto riportati e/o nel Catalogo degli insegnamenti (che può essere filtrato anche per lingua di erogazione tramite la Ricerca avanzata).

Modalità di inserimento a libretto: se l'insegnamento è compreso tra quelli sottoelencati, lo studente può inserirlo autonomamente durante il periodo in cui il piano di studi è aperto; in caso contrario, lo studente deve fare richiesta alla Segreteria, inviando a carriere.scienze@ateneo.univr.it il modulo nel periodo indicato.

2. Attestato o equipollenza linguistica CLA

Oltre a quelle richieste dal piano di studi, per gli immatricolati dall'A.A. 2021/2022 vengono riconosciute:

  • Lingua inglese: vengono riconosciuti 3 CFU per ogni livello di competenza superiore a quello richiesto dal corso di studio (se non già riconosciuto nel ciclo di studi precedente).
  • Altre lingue e italiano per stranieri: vengono riconosciuti 3 CFU per ogni livello di competenza a partire da A2 (se non già riconosciuto nel ciclo di studi precedente).

Tali cfu saranno riconosciuti, fino ad un massimo di 6 cfu complessivi, di tipologia F se il piano didattico lo consente, oppure di tipologia D. Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

Gli immatricolati fino all'A.A. 2020/2021 devono consultare le informazioni che si trovano qui.

Modalità di inserimento a librettorichiedere l’attestato o l'equipollenza al CLA e inviarlo alla Segreteria Studenti - Carriere per l’inserimento dell’esame in carriera, tramite mail: carriere.scienze@ateneo.univr.it

3. Competenze trasversali

Scopri i percorsi formativi promossi dal TALC - Teaching and learning center dell'Ateneo, destinati agli studenti regolarmente iscritti all'anno accademico di erogazione del corso https://talc.univr.it/it/competenze-trasversali

Modalità di inserimento a libretto: non è previsto l'inserimento dell'insegnamento nel piano di studi. Solo in seguito all'ottenimento dell'Open Badge verranno automaticamente convalidati i CFU a libretto. La registrazione dei CFU in carriera non è istantanea, ma ci saranno da attendere dei tempi tecnici.  

4. Periodo di stage/tirocinio

Oltre ai CFU previsti dal piano di studi (verificare attentamente quanto indicato sul Regolamento Didattico): qui informazioni su come attivare lo stage. 

Verificare nel regolamento quali attività possono essere di tipologia D e quali di tipologia F.

Insegnamenti e altre attività che si possono inserire autonomamente a libretto

 

1° periodo lezioni (1A) From 9/16/21 To 10/30/21
years Modules TAF Teacher
The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
Primo semestre From 10/4/21 To 1/28/22
years Modules TAF Teacher
1° 2° Data Analysis for Biomedical Sciences D Gloria Menegaz (Coordinatore)
1° 2° Introduction to Robotics to students of scientific courses. D Paolo Fiorini (Coordinatore)
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
Modules borrowed from the Faculty of Giurisprudenza
1° periodo lezioni (1B) From 11/5/21 To 12/16/21
years Modules TAF Teacher
The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
Secondo semestre From 3/7/22 To 6/10/22
years Modules TAF Teacher
1° 2° Introduction to Robotics to students of scientific courses. D Paolo Fiorini (Coordinatore)
1° 2° Introduction to 3D printing D Franco Fummi (Coordinatore)
1° 2° HW components design on FPGA D Franco Fummi (Coordinatore)
1° 2° Rapid prototyping on Arduino D Franco Fummi (Coordinatore)
1° 2° Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Python programming language D Giulio Mazzi (Coordinatore)

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Graduation


Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti