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 |
|---|---|---|
| I sem. | Oct 3, 2016 | Jan 31, 2017 |
| II sem. | Mar 1, 2017 | Jun 9, 2017 |
| Session | From | To |
|---|---|---|
| Sessione invernale Appelli d'esame | Feb 1, 2017 | Feb 28, 2017 |
| Sessione estiva Appelli d'esame | Jun 12, 2017 | Jul 31, 2017 |
| Sessione autunnale Appelli d'esame | Sep 1, 2017 | Sep 29, 2017 |
| Session | From | To |
|---|---|---|
| Sessione estiva Appelli di Laurea | Jul 19, 2017 | Jul 19, 2017 |
| Sessione autunnale Appelli di laurea | Oct 18, 2017 | Oct 18, 2017 |
| Sessione invernale Appelli di laurea | Mar 21, 2018 | Mar 21, 2018 |
| Period | From | To |
|---|---|---|
| Festa di Ognissanti | Nov 1, 2016 | Nov 1, 2016 |
| Festa dell'Immacolata Concezione | Dec 8, 2016 | Dec 8, 2016 |
| Vacanze di Natale | Dec 23, 2016 | Jan 8, 2017 |
| Vacanze di Pasqua | Apr 14, 2017 | Apr 18, 2017 |
| Anniversario della Liberazione | Apr 25, 2017 | Apr 25, 2017 |
| Festa del Lavoro | May 1, 2017 | May 1, 2017 |
| Festa della Repubblica | Jun 2, 2017 | Jun 2, 2017 |
| Vacanze estive | Aug 8, 2017 | Aug 20, 2017 |
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.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
Bloisi Domenico Daniele
domenico.bloisi@univr.it
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.
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year
| Modules | Credits | TAF | SSD |
|---|
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 (2017/2018)
Teaching code
4S004554
Academic staff
Coordinatore
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
II sem. dal Mar 1, 2018 al Jun 15, 2018.
Learning outcomes
The course deals with the major sources of medical imaging data (X-rays, CT, MRI, PET and US) and provides the students with a flavour of the current methods used to process medical images, enhance their quality and extract useful information from them. A particular focus will be given to diffusion MRI, as it represents a very rich imaging modality that will allow us to investigate several analysis techniques starting from the same data, at increasing levels of complexity.
These concepts are also illustrated in hands-on sessions where these techniques are applied to practical situations and problems that often arise when analyzing real medical images. The laboratory activities will be based on the Python language.
Program
(1) Basic concepts
- Image properties: pixel vs voxel, spatial resolution, orientation, data type etc
- File formats: DICOM, NIFTI, MINC etc
- Signal-to-noise (SNR) vs Contrast-to-noise (CNR) ratio
- Noise, blurring and modality-specific artifacts
- Signal representation: frequency domain, spherical harmonics, sparse bases
(2) Overview of major medical imaging modalities
- Radiography: X-rays projection, fluoroscopy and computed tomography (CT)
- Nuclear medicine: SPECT and PET
- Ultrasound imaging (US)
- Magnetic Resonance Imaging (MRI)
(3) Basic image processing
- Recall of elementary tools: filtering, edge detection and image enhancement
- Registration: features, similarity measures, transformations (linear vs non-linear)
(4) Connectivity analysis with diffusion MRI
- Principles and main applications
- Local reconstruction: DTI, DSI, CSD etc
- Tissue microstructure estimation: axon diameter mapping, AxCaliber, ActiveAx, CHARMED, NODDI etc
- Tractography: local vs global methods, probabilistic, recent advances
(5) Laboratory
- Introduction to Python
- Hands-on activities on the topics covered throughout the course
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| Ravishankar Chityala | Image processing and acquisition using Python (Edizione 1) | Chapman and Hall/CRC | 2014 | 9781466583757 | |
| Andrew Webb | Introduction to biomedical imaging | Wiley-IEEE Press | 2003 | 978-0-471-23766-2 | |
| Jerrold T. Bushberg | The Essential Physics of Medical Imaging (Edizione 3) | Lippincott Williams & Wilkins | 2011 | 0781780578 |
Examination Methods
The grade will be based on a discussion about the final project assigned during the course. The final project is a very important part of the course, as it allows students to synthesize the concepts learned throughout the course, understand the motivation behind each modality, experiment typical problems that arise in daily-life medical images and apply the appropriate techniques to improve image quality and extract useful information.
Bibliography
Type D and Type F activities
Modules not yet included
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.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.
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.
