Introduction to Biological Imaging
Course ME002 in WS 2018/9
General Data
| Course Type | lecture |
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| Semester Weekly Hours | 3 SWS |
| Organisational Unit | Chair of Biological Imaging - Cooperation with Helmholtz Zentrum München (Prof. Ntziachristos) |
| Lecturers |
Vasilis Ntziachristos |
| Dates |
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | The course is designed to be an entry point into a highly dynamic field of modern biomedical imaging, where Engineering meets and merges with the Life Sciences. The course presents the fundamental principles and engineering background of image formation, as it is applied in modern Biology and Medicine. It discusses the hardware and the mathematical and physical basis of image acquisition and reconstruction for state-of-the-art imaging techniques, including optical microscopy, X-ray and X-ray Computed Tomography, Magnetic Resonance Imaging, Nuclear Imaging, ultrasound and optoacoustic methods. Emphasis is placed on connecting the content of the generated imaged to biology and medical needs, driving advanced prognostic, diagnostic and therapeutic decisions. Whenever possible, the course further outlines the complementation of Engineering and Biology as a major force required for advancing medical solutions. The course includes practical application exercises using Matlab and the reading of outstanding scientific publications. The course provides basic knowledge in the following areas: Physics of biomedical imaging: - physical principles and hardware components of modern imaging technologies - relation of wave propagation in tissues and image formation Mathematics and computation in biomedical imaging: - principles of forward modelling and inversion / image reconstruction - algorithm implementation in Matlab - information content and machine learning in imaging Applications of biomedical imaging: - next-generation imaging technologies - application areas of anatomical, functional and molecular imaging This course is intended for Senior Diploma or Bachelor’s electrical engineering students and for Master’s electrical engineering students and serves as an introduction to the utilization of engineering methods into biological imaging, in particular the development of imaging methods for biological and medical imaging. The course focuses on the fundamental principles of image formation, the sources of tissue contrast and the corresponding technological implementations that allow application in modern research and healthcare. Image processing and image rendering are related technologies that are mentioned but are not exhaustively covered in this course but in other lectures by the department. The introduction to imaging begins by justification of the field of imaging in the biological and medical sciences and description of structural, functional and molecular imaging. Principle biological and medical needs, as well as fundamental contrast mechanisms are presented. Basic mathematics and engineering principles of tomography and image formation and reconstruction are then described. The course then outlines major imaging methods, in an exemplary form, used for in-vivo cellular, animal and human imaging including conventional and laser scanning microscopy, X-ray CT, Magnetic Resonance Imaging, Nuclear Imaging and Optical and Photo-acoustic Tomography, including common hardware and transducer implementation and typical applications. Lectures conclude with summarizing unifying principles and application regimes of imaging. Theoretical labs and hand-on laboratory with advanced photonic imaging methods are offered throughout the course. |
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| Links |
Course documents E-Learning course (e. g. Moodle) TUMonline entry |
Equivalent Courses (e. g. in other semesters)
| Semester | Title | Lecturers | Dates |
|---|---|---|---|
| WS 2017/8 | Introduction to Biological Imaging |
Wed, 16:30–18:00 |