Diagnostic Technologies

This course integrates engineering concepts and information technology techniques relevant to medical diagnostics and imaging. It introduces the fundamentals of selected human body systems from an anatomy and physiology perspective and examines their relationship to the physical principles underlying diagnostic radiology.

The course covers the operating principles of major imaging modalities, including X-ray, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Ultrasound, as well as selected diagnostic and material characterization technologies. Students will learn how these technologies are selected based on their functional characteristics and performance criteria.

The course also introduces computer-assisted digital imaging, image processing techniques, and intelligent image analysis methods. Through classroom tutorials, case studies, demonstrations, and practical implementations, students will gain experience in image acquisition, processing, visualization, analysis, and interpretation, preparing them to address challenges in modern diagnostic imaging systems.

The course is designed to:

• Address the fundamentals of human body systems in relation to the physical principles and design of typical bio-mechatronic diagnostic techniques.
• Appraise and understand the physical and operating principles of various imaging modalities, devices, and systems used in medical and industrial applications as representative case studies.
• Study system models, ISO standards, and the classification of medical diagnostic devices in terms of safety and regulatory regimes worldwide.
• Introduce intelligent methods for digital image processing and image analysis.

After completing this course, students should be able to:

• Understand the fundamental principles of various human body systems in relation to the physical principles and design of typical diagnostic techniques.
• Familiarize themselves with the functional understanding of various radiological modalities and techniques used in medical diagnosis.
• Build and apply selection criteria for a given application scenario and analyze it for optimal use.
• Appraise and implement several functions and deep-learning techniques involved in image acquisition, conditioning/processing, display, and analysis.
• Understand system models, ISO standards, and the classification of medical diagnostic devices in terms of safety and regulatory regimes worldwide, including their relation to the development and deployment (entrepreneurial aspects) of new devices (without predicates).

• Diagnostic Radiology Physics: A Handbook for Teachers and Students. American Association of Physicists in Medicine, International Atomic Energy Agency, Vienna, 2014.
• Benseler, J. S. The Radiology Handbook: A Pocket Guide to Medical Imaging. Ohio University Press.

Additional journal articles, book chapters, and reference materials will be provided during the classes as and when required.