This course studies the fundamental architecture of medical imaging systems that use ionizing radiation. It analyzes the components of Diagnostic Radiology systems (Conventional Radiography, Mammography, and Computed Tomography—CT) and Nuclear Medicine imaging (gamma camera, SPECT, PET). Core concepts include:

• • Interactions of photons (X-rays, gamma rays) and high-energy particles with matter
  • X-ray and radioisotope production methods
  • Types of radioactivity and attenuation in tissues and detectors
  • Specialized X-ray imaging techniques
  • Photon-counting imaging techniques (nuclear imaging detectors, gamma radiation)
    The course includes a laboratory exercise on gamma-photon spectroscopy with a NaI:Tl detector and individual assignments/presentations on contemporary and hybrid imaging methods.

Upon completion, students will:

1. Understand fundamental interaction mechanisms of photons and high-energy particles with matter.
2. Gain a comprehensive view of medical imaging systems using ionizing radiation.
3. Describe and distinguish the subsystems (block diagrams) of a complete imaging system.
4. Understand principles of operation to compare and evaluate different medical imaging modalities.
5. Develop research skills through literature review/presentations and hands-on gamma spectroscopy with a NaI:Tl detector, including collaborative activities.

1. Develop advanced knowledge in biomedical instrumentation, neuromechanics, and implant technology.
2. Design and critically analyze complete biomedical systems, assessing performance and proposing improvements.
3. Solve complex technical problems and optimize biosignal acquisition systems in varied environments.
4. Design and implement digital systems with microcontrollers/microprocessors, ensuring functionality, safety, and performance.
5. Program, test, and optimize software for end-to-end biosignal management.
6. Work autonomously and collaboratively in multidisciplinary settings, contributing to process and know-how improvements.

1. Attain in-depth understanding of roles and applications of biomedical engineering in the job market, evaluating career paths and prospects.
2. Analyze the field’s interdisciplinarity and its convergence with medicine and technology, assessing contributions to innovative projects and ventures.
3. Critically evaluate current trends, challenges, and strategies, proposing evidence-based actions for new entrepreneurial initiatives in biomedical engineering.

1. Achieve a comprehensive understanding of emergency medicine and its supporting medical technology, distinguishing equipment for vital support, patient transport, and extrication.
2. Differentiate among equipment categories for vital support, transport, and extrication.
3. Understand European quality and performance standards for emergency medicine, staff/patient safety, and medical devices.
4. Describe transport and evacuation means (vital support, transfer, extrication) used in emergency medicine.
5. Understand key aspects of medical evacuation (MEDEVAC) under extreme conditions, including available extrication/stabilization means and supporting devices.

1. Deeply analyze and evaluate fundamentals of control systems and HMI in biomedical engineering.
2. Independently design mathematical models of biological processes and develop functional digital control systems (e.g., Arduino).
3. Design and assess health interfaces grounded in usability, accessibility, and user experience.
4. Apply evaluation methodologies and performance metrics, analyze data, and draw evidence-based conclusions.
5. Communicate technical concepts and design decisions clearly via reports, presentations, and prototypes to varied audiences.
6. Manage complex HMI/control projects, improving processes, disseminating knowledge, and driving innovation.

Minos Matsoukas, Assistant Professor, Department of Biomedical Engineering, University of West Attica, Greece

1. Master core bioinformatics concepts for basic and translational research problems.
2. Develop foundational programming skills in R.
3. Understand and execute large-omics data analysis at a professional level, selecting appropriate tool parameters.
4. Build specialized problem-solving skills in computational biology for academia, research centers, and bio/pharma industries.
5. Develop knowledge-discovery capabilities across large omics databases.

1. Understand theory and implementation technologies for acquisition, visualization, processing, and analysis of medical signals and images.
2. Comprehend methods used in modern computational systems for medical imaging and instrumentation.
3. Distinguish and select appropriate processing/analysis methods for different medical systems.
4. Implement DSP and image-processing algorithms in code and build complete software systems using modern technologies.

Upon successful completion, students will be able to:

1. Demonstrate deep understanding of core biomechanics principles and key definitions/concepts.
2. Describe and distinguish types and applications of prosthetic, orthotic, and robotic systems for upper and lower limbs.
3. Analyze mechanical forces and motions in the musculoskeletal system and evaluate human performance using quantitative and qualitative methods.
4. Understand basic robotics principles and human–assistive system interfaces.
5. Apply ergonomics and kinesiology to assess or improve human function.
6. Recognize modern rehabilitation technologies and methods, including computational simulations and models.