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Image Acquisition Methods
Motivation: The course is designed as a supplement for image processing lectures, to be attended before, after or parallel to them. In order to choose the right image processing methods for a given image, it is important to know what the image data represents and what specific properties it possesses.
Teaching Goals: In this lecture, participants learn:
- what digital images are,
- how they are acquired,
- what they encode and what they mean,
- which limitations are introduced by image acquisition.
Contents: A broad variety of image acquisition methods is described, including imaging by virtually all sorts of electromagnetic waves, acoustic imaging, magnetic resonance imaging and more. While medical imaging methods play an important role, the overview is not limited to them.
Hybrid Lectures: Participate in person or via MS Teams. Recordings will be made available.
Monday 12:15-14:00, E1.3, HS001
First lecture: 21.10.2024
Entrance Requirements
Basic mathematics courses are recommended.
Basic knowledge in physics is helpful, but the lecture is designed to be self-sufficient in this regard.
Tutorials
Assignments are designed for group work. You are encouraged to connect with your fellow students and solve the problems together. The lecturer will be available to assist you and check your solutions. For all assignments, a written solution is also offered online. Please select a tutorial slot upon registration. You can join the group roulette to be randomly assigned to a team of other students in your selected tutorial slot.
If you have questions concerning the tutorials, please do not hesitate to contact Pascal Peter.
Assessments / Exams
There will be two closed book written exams:
The first written exam will take place on 10.02.2024 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
The second written exam will take place on 01.04.2025 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
You can find the detailed rules for our exams in the self test assignment in the CMS materials. (Published in the beginning of the semester.)
You can participate in both exams, and the better grades counts if your course of study allows that. Please remember that you have to register online for the exam in the HISPOS/LSF system.
If you cannot attend the exam, contact Pascal Peter as early as possible. In case you have proof that you cannot take part for medical reasons or you have another exam on the same day, we can offer you an oral exam as a replacement. Note that we need written proof (e.g. a certificate from a physician/Krankenschein) for the exact date of the exam.
Lecture notes / Assignments
Lecture content in form slides and assignments are available for download online via CMS in the beginning of the semester. Access will be granted after registration.
References
- B. Jähne, H. Haußecker, P. Geißler, editors, Handbook of Computer Vision and its Applications. Volume 1: Sensors and Imaging. Academic Press, San Diego 1999.
- S. Webb, The Physics of Medical Imaging. Institute of Physics Publishing, Bristol 1988.
- C. L. Epstein, Introduction to the Mathematics of Medical Imaging. Pearson, Upper Saddle River 2003.
- R. Blahut, Theory of Remote Image Formation. Cambridge University Press, 2005.
- A. C. Kak, M. Slaney, Principles of Computerized Tomographic Imaging. SIAM, Philadelphia 2001.
- Articles from journals and conferences.
Further references will be given during the lecture.