Learning objectives

DIAGNOSTIC IMAGING

To teach the contribution of diagnostic imaging modalities (Conventional Radiology, Ultrasonography, Computed Tomography, Magnetic Resonance, Nuclear Medicine) in evaluating organs and systems and their diseases. The student will need to grasp the basic notions of the interaction of x-rays, ultrasound, radio waves with normal and pathological biological tissues, together with their risks, including radiation, and costs. After attending this course, the student will be able to discuss the main clinical indications of imaging with different modalities and the diagnostic approach to the study of the different organs.


• Physical principles underlying of conventional radiology, computed tomography, ultrasonography, magnetic resonance and nuclear medicine
• CT and MR technology: state-of-the-art and upcoming technologies
• Digital systems for image visualization and processing and for reporting. CAD software. Radiomics principles and software. Legal issues on image and data sharing
• Contrast agents: pharmacology, rationale of use, mode of administration, contraindications, adverse effects
• Respiratory imaging
• Cardiovascular imaging
• Gastrointestinal Imaging
• Hepato-bilio-pancreatic imaging
• Genitourinary imaging
• Breast Imaging
• Central Nervous System Imaging
• Basics of interventional radiology
• Basics of radiobiology. Deterministic and stochastic effects. Radiation protection.
• Basics of Nuclear Medicine.
• Current use and future developments of Artificial Intelligence in Diagnostic Imaging

Artificial Intelligence for Image Processing Module.
The module aims to introduce the main techniques for extracting diagnostic information from biomedical imaging data, effectively visualizing data of different types, and reconstructing measurable three-dimensional models from the data.

Diagnostic Imaging Tutorials

The small group activities aim to familiarize students with the environments in which diagnostic investigations and imaging-based therapeutic procedures are performed and the practical approach to the interpretation of diagnostic imaging exams.

Examination Methods

Oral examination finalized to verify the knowledge of the course contents. Artificial Intelligence Verification of learning will be carried out through: - written test with questions and exercises - evaluation of laboratory activities

Evaluation criteria

The test verifies the level of knowledge of the theoretical contents and the ability to use language in describing the contents of the program. The exam is passed with a score equal to or greater than 18/30. Artificial Intelligence At the end of the course, the student must be able to: -understand the fundamentals of the primary diagnostic image processing, 2D and 3D segmentation and reconstruction and visualization algorithms, -evaluate the performance of different image processing and visualization methodologies applied in medicine and choose the most appropriate approach for a specific problem, -analyze the design choices of a medical decision support system based on the processing and display of diagnostic images. The final grade will be represented by the weighted average over the number of CFUs of the grades given to the different exams.