Lecture (2h) with exercises (2h)
6 credit points

Lectures: Recorded Digital Lectures + Live Q&A
Thursday 10-12 c.t.
First Q&A: Thursday, October 28, 2021

Tutorials: Virtual Group Work with Lecturer Assistance
Slot 1: Monday 8:30-10 s.t.
Slot 2: Monday 10-12 c.t.

First Tutorial: Monday, November 8, 2021

Announcements – Description – Entrance requirements – Tutorials – Exams
Lecture notes/Assignments – References

01/11/2021 Registration is now closed.
04/10/2021 Update on the Lecture Mode: In order to enable participation for all students, the course will be fully digital as anticipated in the previous announcement. We will use Microsoft Teams as a communication and content hub for the lecture. Regular teaching will begin on Thursday, October 28, 2021, but you can already register for the course to gain early access to Teams. This also gives you access to an introduction video that can help you to decide if this lecture is interesting to you.

06/08/2021 Website is online

Registration for this lecture was open until Sunday, Oct 31, 2021. Keep in mind that in most courses of studies, you also have to register via the HISPOS system of the Saarland University

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: Therefore, 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.

In case you want to get a better idea if this course is the right one for you, register and watch the introduction video on the Teams file repository.

Basic mathematics courses are recommended.
Basic knowledge in physics is helpful, but the lecture is designed to be self-sufficient in this regard.

Assignments are designed for group work. You are encouraged to connect with your fellow students either in person in classroom assignments and/or online with Teams, depending on the mode of the lecture. The lecturer will be available to assist you and check your solutions. Assignments are not graded, but you have to demonstrate active participation to be admitted to the exam. For all assignments, a written solution is also offered online.

If you have questions concerning the tutorials, please do not hesitate to contact Pascal Peter.

There will be two closed book written exams:

The first written exam will take place on Monday, February 14, 2022 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
The second written exam will take place on Thursday, March 31, 2022 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.

Please note that due to the dynamics of the Sars-Cov2 pandemic, changes to the exam schedule or mode might be necessary. You can find the detailed rules for our exams in the self test assignment in the Teams file repository.
You can participate in both exams, and the better grades counts. Please remember that you have to register online for the exam in the HISPOS system of the Saarland University.

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 content in form of videos, slides, and assignments are available for download via Microsoft Teams. Access will be granted after registration. Note that the initial registration requires manual confirmation and can thus be delayed a bit.

The assignments and the source code needed for the programming assignments will be provided here during the semester.

• 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.