Diagnostic Imaging Techniques

Sustainable Development Goals (SDG)

• 3. Good health and well-being
• 4. Quality education

Objectives

The main objective of this subject is to provide students with an understanding of the main medical imaging techniques used in clinical diagnosis.

Through theoretical classes, students learn the physical foundations, associated risks, clinical applications and technological advances in the field of diagnostic imaging.

The objectives are:

• Understand the history and evolution of medical imaging techniques.
• Know the physical foundations of imaging diagnostic techniques.
• Analyze clinical cases using different imaging techniques:
  • Radiography by projection
  • Computed tomography
  • Nuclear medicine
  • Ultrasound imaging
  • Magnetic resonance
  • Multimodality image
  • others
• Assess the associated risks.
• Know the basic principles of computer vision in the application of image diagnostics.
• Introduce the applications of machine learning and deep learning in image diagnostics.

Learning outcomes

• RA1. Acquire and demonstrate advanced knowledge of theoretical and practical aspects and work methodology in the field of biomedicine.
• LO2. Correctly recognize the morphology and structure of tissue, organs and systems with imaging techniques.
• LO3. Learn about the main research methods used in forensic medicine.
• LO4. It applies imaging techniques to the analysis of the functioning of the organism at different hierarchical levels.

Skills

General skills

• Carry out professional activities independently with initiative and respect for other health professionals.
• Formulate hypotheses following the scientific method, with an ability to summarize and analyze information in a critical way in order to be able to solve problems.

Specific skills

• Apply the principles of chemistry and physics to the interpretation of biological phenomena and in the development of relevant biomedical technology.
• Evaluate technological advances for the diagnosis, prognosis and treatment of disease.
• Use key analytical and imaging techniques, and basic technological instruments, following customary preclinical research laboratory protocols.

Basic skills

• Students can apply their knowledge to their work or vocation in a professional manner and have competencies typically demonstrated through drafting and defending arguments and solving problems in their field of study.
• Students have demonstrated knowledge and understanding in a field of study that builds on general secondary education with the support of advanced textbooks and knowledge of the latest advances in this field of study.
• Students have the ability to gather and interpret relevant data (usually within their field of study) in order to make judgments that include reflection on relevant social, scientific and ethical issues.

Core skills

• Bring to bear values of entrepreneurship and innovation in one's academic and professional careers.
• Exercise active citizenship and individual responsibility with a commitment to democratic values and sustainable development.
• Make use of professional skills in multidisciplinary, complex, networked environments, whether on-site or online.
• Reflect critically on knowledge of all kinds, with a commitment to professional rigor and quality.

Content

The subject is designed to offer a complete and detailed overview of the most important medical imaging techniques used in clinical diagnosis. Below are the main contents covered throughout the course:

• History and evolution of medical imaging techniques
  • Historical development of medical imaging techniques
  • Impact of technological innovations in clinical diagnosis
• Physical foundations of imaging diagnostic techniques
  • Basic physical principles of the different techniques
  • Interaction of radiation with biological matter
• Imaging techniques and their clinical applications
  • Radiography by projection
    • Principles of operation
    • Clinical applications
  • Computed Tomography (CT)
    • Fundamentals of CT
    • Clinical use and case examples
  • Nuclear medicine
    • Use of radioisotopes
    • Diagnostic and therapeutic applications
  • Ultrasound imaging
    • Generation and detection of ultrasound
    • Clinical applications and benefits
  • Magnetic Resonance (MRI)
    • Fundamentals of MR
    • Clinical applications and examples
  • Multimodality image
    • Integration of various imaging techniques
    • Benefits in diagnosis and treatment
• Assessment of associated risks
  • Risks of exposure to ionizing radiation
  • Security measures and protocols to minimize risks
• Basic principles of computer vision
  • Introduction to computer vision
  • Applications in imaging diagnostics
• Applications of machine learning and deep learning
  • Fundamentals of machine learning and deep learning
  • Applications in imaging diagnostics
  • Practical examples of implementation and results

Evaluation

The evaluation criteria are:

• Participation observation: 5%
• Follow-up of work done: 15%
• Carrying out work: 30%
• Specific assessment tests: 50% (divided into a partial exam and a final exam in equal parts (25% each); recoverable activity

All activities must exceed 4.0 in order to make the weighted average. And, in the case of specific assessment tests or exams, the average of each of them must be 5 or higher.

In the recuperation phase, the student can access recuperable activities as long as they do not exceed 50% of the subject.

important

Plagiarism or copying someone else's work is penalized at all universities and, according to the UVic-UCC Coexistence Rules , constitutes serious or very serious offences. Therefore, in the course of this subject, plagiarism or the misappropriation of other people's texts or ideas (see what is considered plagiarism ) and the improper or undeclared use of artificial intelligence in an activity are translated automatically in suspension or other disciplinary measures.

To cite texts and materials appropriately, consult the academic citation guidelines and guidelines available on the UVic Library website.

Methodology

The teacher gives theoretical and problem classes. The student must do problems and exercises for each topic and must prepare beforehand some of the exercises that are done in class. The student can have explanatory modules, which he can obtain through the Virtual Campus, in a format closer to class notes than to a textbook.

During the practices/exercises, the necessary material is provided to be able to do them. It is convenient for the student to be able to use a personal computer. In addition to the face-to-face component of the internships, they must be accompanied by a report.

Bibliography

Key references

• Bankman, I. N. (Isaac N.) (200). Handbook of medical imaging processing and analysis. Retrieved from https://ucercatot.uvic-ucc.cat/permalink/34CSUC_UVIC/qq5d82/alma991001156533006718
• Meyer-Bäse, Anke. (2004). Pattern recognition in medical imaging. Retrieved from https://ucercatot.uvic-ucc.cat/permalink/34CSUC_UVIC/qq5d82/alma991000995375806718
• Nadeski, Mark. Future of medical imaging (2014). Medical imaging : technology and applications. Retrieved from https://ucercatot.uvic-ucc.cat/permalink/34CSUC_UVIC/qq5d82/alma991000855709706718

Further reading

Teachers will provide complementary bibliography and compulsory reading throughout the course via the Virtual Campus.