Unit PHYSICAL SCIENCES

RADIATION PHYSICS

Code	A000082
CFU	2
Teacher	Andrea Orecchini
Teachers	Andrea Orecchini
Hours	24 ore - Andrea Orecchini
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	FIS/07
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Electromagnetic radiations. Corpuscular radiations. Structure of the atom. Nuclides and isotopes. Radioactivity. Radiation-matter interactions. X-ray production and attenuation. Attenuation of charged particles.
Reference texts	- Faiz M. Khan, The Physics of Radiation Therapy - Joseph Selman, The Basic Physics of Radiation Therapy - Harold E. Johns and John R. Cunningham, The Physics of Radiology
Educational objectives	Ionizing radiations are the main tool the future TSRMs will work with. The aim of the course is thus to provide the basic knowledge of radiation physics, which will allow the students to understand the working principles of the instruments and devices, with which they will work during both their subsequent studies and their professional life.
Prerequisites
Teaching methods	Face-to-face lectures.
Other information
Learning verification modality	The student can choose between two alternative examination methods: a) a written exemption test, taken shortly after the end of the lectures of the radiation physics module; b) an oral examination, after the end of the semester, on the official exam dates. Given the propedeuticity of the radiation physics module, the exemption test method (a) is strongly encouraged.
Extended program	Radiations: definition and some examples. Electromagnetic radiation: basic properties, wavelength-frequency relationship, energy and photons. Spectrum of lectromagnetic waves. Corpuscular radiations. Properties of the main corpuscular radiations. Associated wavelength. Structure of the atom. Bohr atom and electronic energy levels. Periodic table of elements. Nuclides and isotopes. Nuclides stability curve. Example of radiation emission from electronic levels (keV). Nuclear shell model. Example of radiation emission from nuclear levels (MeV). Radioactivity: definition and qualitative physical origin. Exponential law of radioactive decay. Decay constant. Activity and specific activity. Mean life and half time. Radioactive equilibrium: transient equilibrium and secular equilibrium. Examples of transient and secular equilibria of relevance to medical radiology. Natural radioactive series. X-ray production processes. Conceptual diagram of an X-ray tube. Spectrum of an X-ray tube. Direct and indirect ionizing radiation. Attenuation of a monochromatic photon beam: linear attenuation coefficient and half-value layer. Energy dependence of the attenuation coefficient and filter effect on non-monochromatic beams. Mass attenuation coefficient. Main photon-matter interactions of relevance to radiology: coherent scattering, photoelectric effect, Compton effect, pair production. Energy dependence of the mass attenuation coefficient: notable examples. Charged particles interactions. Speed dependence of the ionizing power; Bragg peak.

PHYSICS

Code	50011800
CFU	1
Teacher	Andrea Orecchini
Teachers	Andrea Orecchini
Hours	12 ore - Andrea Orecchini
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	FIS/07
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Fluids, Thermodinamics, Electricity Magnetism Waves
Reference texts	D.Halliday, R.Resnick, J.Walker, Fondamenti di Fisica, ed. C.E.A.
Educational objectives	The student must demonstrate a thorough knowledge of the arguments developed in the program.
Prerequisites	Knowledge of basic elements of maths, informatics and English language
Teaching methods	Lessons
Learning verification modality	Written test to demonstrate knowledge of subjects and ability to solve elementary excercises.
Extended program	Fluid mechanics, pressure, Pascal's principle, Stevin's law and hydrostatic pressure, Archimede's law, Bernouilli's law, Poiseuille's law and viscosity coefficient, Thermology: heat and temperature, effects of heat: heating and specific heat, phase transformation and latent heat, saturated vapor pressure and boiling temperature; heat flow and thermal balance law; heat propagation mechanisms: conduction, convection and radiation, Waves: general, propagation speed, frequency, wavelength, harmonic waves, superposition principle Radiation: power and intensity of a wave, photons, ionizing and non-ionizing radiation Electrostatics: electric force, electric field: electric field vector, electric potential, field lines and equipotential surfaces, electric field sources, effects of the electric field on dielectrics and on conductors, electrical capacity of a conductor; Electric currents: electric current intensity, Ohm's laws and electric resistance, Joule effect, electric circuits, series and parallel connections of resistors and capacitors; Magnetism: magnetic induction vector, Lorentz force, magnetic field sources: magnets and Ampere law, Electromagnetic field: electromagnetic induction, magnetic flux, electromotive force, origin of electromagnetic waves.

INFORMATICS

Code	GP003730
CFU	2
Teacher	Andrea Orecchini
Teachers	Ivan Gerace (Codocenza)
Hours	24 ore (Codocenza) - Ivan Gerace
Learning activities	Base
Area	Scienze propedeutiche
Academic discipline	INF/01
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Digital representation of images. Introduction to the C programming language. Management of digital images using C programming language.
Reference texts	Gonzalez, Woods, "Digital Image Processing", Prentice Hall, Pearson Education. Kochan, "Programming in C", Adisson-Wesley.
Educational objectives	At the end of the course the student must be able to design and write a simple C language program for the management of digital images.
Prerequisites	No one.
Teaching methods	Frontal lesson. Guided lesson at the computer lab. Problem solving.
Learning verification modality	Computer lab test and oral exam.
Extended program	The light. RGB, CMYK, Lab representation. Blur and noise corruption of an image. Punctual, local and global operators for image reconstruction. Quantization problem. Estimation of the optical flow. Separation of components. Tomography. Demosaicing. Variables in C language. Commands for, while and if. File reading and writing. Management of a gray level image. Management and creation of color images.

RESEARCH METHODOLOGY

Code	40285806
CFU	2
Teacher	Andrea Orecchini
Teachers	Donatella Lanari (Codocenza)
Hours	24 ore (Codocenza) - Donatella Lanari
Learning activities	Caratterizzante
Area	Scienze interdisciplinari
Academic discipline	SECS-S/02
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	General information on statistics and its use in medicine. Purposes and methods of statistical analysis, statistical characteristics and classification. DESCRIPTIVE STATISTICS: principles descriptive statistics indexes, their use and their representation Epidemiology and Clinical Trials Probability calculation. INFERENTIAL STATISTICS. Evaluation of data usage and processing. Correlation for the association between qualitative variables. Linear regression. Tables and survival curves.
Reference texts	Fowler J., Jarvis P., Chevannes M.: STATISTICA PER LE PROFESSIONI SANITARIE. Edizioni EdiSES. Availability of teaching materials on the UniStudium platform
Educational objectives	The Statistics module is the only teaching of the CdS statistics and examines the introductory and basic principles necessary for an understanding of the elements of descriptive and inferential statistics. The main objective of the module is to provide students with the knowledge to deal with the management and interpretation of data in the workplace. The main knowledge gained will be: understand and know the main terms of descriptive statistics; know the basics of probability theory; the various aspects of the smooth conduct of clinical trials; how to evaluate the data and their possible processing. The main skills acquired will be organizing, processing, interpreting scientific data produced in the workplace and found in the scientific literature and communicate appropriately the obtained summary information.
Teaching methods	Face-to-face lessons: Classroom lessons on all the topics of the module itself with the use of visual media and discussion with the students.
Learning verification modality	The exam includes an oral exam consisting of a discussion aimed at ascertaining the level of knowledge and understanding reached by the student on the topics presented in class and listed in the programs. The student must demonstrate knowledge the notions basic statistics to be able to read and understand an article, evaluate and use data. The oral test will also verify the communication skills of the student, his command of the language, the ability to apply the acquired skills and develop solutions in independent judgment.
Extended program	General information on statistics and its use in medicine. Purposes and methods of statistical analysis, statistical characteristics and classification. DESCRIPTIVE STATISTICS Measurements and sampling in health studies. Data analysis and presentation. Presentation of the results of tables. Main graphic representation (ortogrammi, histograms etc.). absolute frequencies, relative, cumulative. Distribution of frequencies. Measures of central tendency. variability of the measurement. Curves of symmetric and asymmetric frequencies. EPIDEMIOLOGY Frequency measures of disease: prevalence and frequency. Types of studies. Confounding. CLINICAL TRIALS History, nature of clinical trials. types of clinical trials. Ethical aspects. Smooth conduct of a clinical trial. Probability calculation'. Definition and calculation of the probability theory. Event and event space. The measure of probability. basic principles of probability. Bayes theorem and applications. Specificity and sensitivity. positive predictive value, negative predictive values. relative risk and odds-ratio. ROC-curves and their interpretation. empirical law of the case. Theoretical probability distributions: Gaussian and binomial and Poisson. Applications. INFERENTIAL STATISTICS. Outline of the central limit theorems. standard error. Levels of significance. Confidence intervals. standard normal distribution and T-student distribution. Testing hypotheses: the concept of hypothesis, error of first kind and II species. power of the test. Tests based on a sample. Z test for the mean. One-tailed test and two-tailed. Comparing averages for paired and independent samples. Parametric and non-parametric statistics. Analysis of variance. How to use the t-test to identify differences between groups. Test for multiple comparisons. Test ¿2: meaning, properties and applications. Correlation for the association between qualitative variables, Pearson coefficient, Spearman coefficient. Linear regression. Tables and survival curves.