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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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Semester 1 | Oct 2, 2023 | Jan 26, 2024 |
Semester 2 | Mar 4, 2024 | Jun 14, 2024 |
Session | From | To |
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Winter exam session | Jan 29, 2024 | Mar 1, 2024 |
Summer exam session | Jun 17, 2024 | Jul 31, 2024 |
Autumn exam session | Sep 2, 2024 | Sep 30, 2024 |
Session | From | To |
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Summer graduation session | Jul 19, 2024 | Jul 19, 2024 |
Autumn graduation session | Oct 21, 2024 | Oct 21, 2024 |
Winter graduation session | Mar 26, 2025 | Mar 26, 2025 |
Period | From | To |
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Festa di Ognissanti | Nov 1, 2023 | Nov 1, 2023 |
Festa dell'Immacolata | Dec 8, 2023 | Dec 8, 2023 |
Vacanze di Natale | Dec 24, 2023 | Jan 7, 2024 |
Festività pasquali | Mar 29, 2024 | Apr 1, 2024 |
Ponte della Festa della Liberazione | Apr 25, 2024 | Apr 26, 2024 |
Festa del Lavoro | May 1, 2024 | May 1, 2024 |
Festività del Santo Patrono: San Zeno | May 21, 2024 | May 21, 2024 |
Festa della Repubblica | Jun 2, 2024 | Jun 2, 2024 |
Vacanze estive | Aug 12, 2024 | Aug 17, 2024 |
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.
Academic staff
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
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2024/2025
Modules | Credits | TAF | SSD |
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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.
Biomedical image processing (2024/2025)
Teaching code
4S004554
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Courses Single
Authorized
The teaching is organized as follows:
Teoria
Laboratorio
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.
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
Type D learning activities are the student's choice, type F activities are additional knowledge useful for job placement (internships, transversal skills, project works, etc.). According to the Teaching Regulations of the Course, some activities can be chosen and entered independently in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F learning activities can be covered by the following activities.
1. Modules taught at the University of Verona
Include the modules listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).
Booklet entry mode: if the teaching is included among those listed below, the student can enter it independently during the period in which the curriculum is open; otherwise, the student must make a request to the Secretariat, sending the form to carriere.scienze@ateneo.univr.it during the period indicated.
2. CLA certificate or language equivalency
In addition to those required by the curriculum/study plan, the following are recognized for those matriculated from A.Y. 2021/2022:
- English language: 3 CFUs are recognized for each level of proficiency above that required by the course of study (if not already recognized in the previous course of study).
- Other languages and Italian for foreigners: 3 CFUs are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).
These CFUs will be recognized, up to a maximum of 6 CFUs in total, of type F if the study plan allows it, or of type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.
Those enrolled until A.Y. 2020/2021 should consult the information found here.
Method of inclusion in the booklet: request the certificate or equivalency from CLA and send it to the Student Secretariat - Careers for the inclusion of the exam in the career, by email: carriere.scienze@ateneo.univr.it
3. Transversal skills
Discover the training paths promoted by the University's TALC - Teaching and learning center intended for students regularly enrolled in the academic year of course delivery https://talc.univr.it/it/competenze-trasversali
Mode of inclusion in the booklet: the teaching is not expected to be included in the curriculum. Only upon obtaining the Open Badge will the booklet CFUs be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.
4. CONTAMINATION LAB
The Contamination Lab Verona (CLab Verona) is an experiential course with modules on innovation and enterprise culture that offers the opportunity to work in teams with students from all areas to solve challenges set by companies and organisations.
Upon completion of a CLab, students will be entitled to receive 6 CFU (D- or F-type credits).
Find out more: https://www.univr.it/clabverona
PLEASE NOTE: In order to be admitted to any teaching activities, including those of your choice, you must be enrolled in the academic year in which the activities in question are offered. Students who are about to graduate in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these graduation sessions are valid for students enrolled in the previous academic year. Therefore, students who undertake an activity in an academic year in which they are not enrolled will not be granted CFU credits.
5. Internship/internship period
In addition to the CFUs stipulated in the curriculum/study plan (check carefully what is indicated on the Teaching Regulations): here information on how to activate the internship.
Check in the regulations which activities can be Type D and which can be Type F.
Modules and other activities that can be entered independently in the booklet
years | Modules | TAF | Teacher |
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1° 2° | Introduction to smart contract programming for ethereum | D |
Sara Migliorini
(Coordinator)
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years | Modules | TAF | Teacher | |
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2° | Programming Challanges | D |
Romeo Rizzi
(Coordinator)
|
|
1° 2° | Python programming language | D |
Carlo Combi
(Coordinator)
|
|
1° 2° | Protection of intangible assets (SW and invention)between industrial law and copyright | D |
Mila Dalla Preda
(Coordinator)
|
years | Modules | TAF | Teacher |
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1° 2° | Cooperative Game Theory in the (Deep) RL Era | D |
Alessandro Farinelli
(Coordinator)
|
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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
Deadlines and administrative fulfilments
For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.
Need to activate a thesis internship
For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.
Final examination regulations
Upon completion of the Master’s degree dissertation, students are awarded 24 CFU, which equates to no more than 4-5 months of full-time work. The dissertation may be written and presented in English or Italian, also using multimedia tools such as presentations and videos.
Goals
The primary goal of a dissertation is to develop an original study that may include an application project or a theoretical topic related to specific design issues, or a critical review of the most recent developments in a given field of study. During the preparation of the dissertation, under the guidance of the Supervisor and co-supervisors (if any), the student is expected to conduct an in-depth study of the chosen topic, while gaining the ability to summarise and creatively apply the knowledge acquired. The dissertation should focus on topics of bioinformatics and medical informatics, or closely related areas of study. The work shall consist in the written presentation of activities that may be structured as follows:
- design and development of applications or systems;
- critical analysis of contributions from the scientific literature;
- original research contributions.
The dissertation may be written either in English or in Italian, and can be presented either in English or in Italian, also relying on multimedia tools such as presentations and videos. Should the dissertation be written in Italian, the work will need to include an abstract in English.
Assessment methods and examination procedures
The final examination consists in writing a Master’s degree dissertation, which will engage the student in a work of research, formalisation, design or development, thus contributing to complete their technical and scientific training. Each dissertation can be either internal or external, depending on whether it is carried out at the University of Verona or in collaboration with another institution. For each dissertation a Supervisor, one or more co-supervisors (optional) and an Examiner will be appointed. The Examiner is appointed by the Computer Science Teaching Committee at least 20 days before the presentation of the dissertation, once the student's eligibility to take the Master's degree examination has been verified. With regard to the legal aspects related to the dissertation and its scientific outcomes (e.g. intellectual property of research outcomes), please refer to the relevant legislation and the University Regulations.
Evaluation of the dissertation
The Supervisor, the co-supervisor/s (if any) and the Examiner will evaluate the dissertation based on the following criteria:
- level of in-depth analysis carried out, in relation to the most recent developments in the areas related to information technology, with a focus on medical and biological applications;
- scientific and/or technological outcomes of the dissertation;
- student’s critical thinking;
- student’s experimental and/or formal development;
- student’s ability to carry out independent work (this point will not be assessed by the Examiner);
- value of the methodologies used;
- accuracy in planning and writing the dissertation.
Graduation mark
The graduation mark (based on a 110-point scale) is a whole value between 66/110 and 110/110 and is calculated by adding together the following elements (then rounding the result to the nearest whole number, e.g. 93.50 => 94; 86.49 => 86):
- 1) the average of the marks gained in the modules, weighted according to CFU, converted to a 110-point scale;
- 2) evaluation of the dissertation and the oral presentation during the final examination, based on the following methods:
- a) each of the points 1-7 listed above will be assigned a coefficient between 0 and 1 (fractional coefficient with one decimal place);
- b) the quality of the presentation will be assessed by awarding a coefficient between 0 and 1 (fractional coefficient with one decimal place);
- c) the sum of the points resulting from (a) and (b).
The Graduation Committee may award one extra point in the following cases: cum laude honours obtained in the exams taken during the degree programme; participation in internships officially recognised by the Computer Science Teaching Committee; taking extra modules; and the achievement of the degree in a time that is shorter than the normal duration of the degree programme. If the final score is 110/110, the Graduation Committee may award cum laude honours by unanimous decision.
External dissertations
An external dissertation is a work carried out in collaboration with an institution/body other than the University of Verona. In this case, the topic of the dissertation must be agreed in advance with a Supervisor from the University of Verona. In addition, the student must indicate at least one co- supervisor belonging to the external institution/body, who will support the student during the work on the dissertation. The Supervisor and the co- supervisors must be indicated in the online graduation application. The insurance aspects relating to the student's stay at the external institution are regulated by the regulations in force at the University of Verona. If the dissertation involves a period of training at the external institution/body, then it is necessary that the University of Verona enters into a specific agreement with such institution/body. The scientific outcomes of the dissertation will be available to all parties involved. In particular, the contents and results of the dissertation are to be considered public. For all matters not strictly scientific (e.g. agreements, insurance) the resolution of the Academic Senate of 12 January 1999 shall be taken as a reference.
Supervisor, co-supervisors, examiners
The dissertation presentation is introduced by the Supervisor. Professors belonging to the Master’s degree programme in Medical Bioinformatics, the Department of Computer Science, and any associated departments may be appointed as Supervisors, as well as any lecturers from the University of Verona whose area of interest is included in the Scientific-disciplinary Sectors (SSD) ING/INF/05 and INF/01. In addition to those who have the above requirements to be appointed as Supervisor, the following individuals may be appointed as co-supervisors: researchers working in external research institutes, research grant holders, post-doctoral fellowship holders, PhD students, technical staff of the Department, external experts appointed by an Italian University, corporate officers who have a remarkable experience in the field relevant to the topic of the dissertation. Examiners may be appointed among professors of the University of Verona, working in the Scientific- disciplinary Sectors (SSD) included in the educational offer of the Master’s degree programme in Medical Bioinformatics, and experts in the specific field of the dissertation topic.
Procedures and deadlines
The student who is about to complete their studies must identify a dissertation topic, proposed or approved by a Supervisor or co-supervisor/s (if any). When the work is nearing completion, the student must submit to the Teaching and Student Services Unit the graduation application, which must contain the title of the dissertation (even provisional), the name of the Supervisor, co-supervisor/s (only for external dissertations) and Examiner. Subsequently, on dates established by the Teaching and Student Services Unit, and in any case no later than 20 days before the graduation, the student must submit the graduation application form with the final title of the dissertation, which must be signed by the Supervisor. These documents must be delivered in accordance with the terms established by the Teaching and Student Services Unit.
The student will need to:
- i) upload a copy of their dissertation on ESSE3;
- ii) send a copy of their dissertation in PDF format to their Examiner.
In order to be admitted to the final examination, the student must have acquired the CFU in the SSD (Scientific-Disciplinary Sectors) set out in the Master’s degree regulations and teaching plan, and be up to date with the payment of their tuition fees. The Teaching and Student Services Unit of the Master's degree programme will invite all the Supervisors and co-supervisors involved, providing them with information about the date and time of the final examination.
Graduation Committee
The Graduation Committee shall include five members, of which at least four are professors in the Master's degree programme in Medical Bioinformatics. Based on the number of graduates, the Computer Science Teaching Committee will identify the most appropriate organisational methods for administering the examination, and it shall make available the calendar of tests at least one week before the examination itself. The procedures and deadlines for the submission of the graduation application are established by the Computer Science Teaching Committee and by the relevant offices.
Career management
Student login and resources
Erasmus+ and other experiences abroad
Tutoring faculty members
Attendance modes and venues
As stated in the Teaching Regulations, attendance at the course of study is not mandatory.
Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.
The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus.
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.