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

Lectures: Digital Video Lectures with Online Q&A Sessions
Friday 12-14 c.t.
First Q&A: Friday, November 6, 2020

Tutorials: Online Group work with Lecturer Assistance
Slot 1: Wednesday 8:30-10 s.t.
Slot 2: Wednesday 10-12 c.t.

First Tutorial: Wednesday, November 11, 2020

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

02/10/2020 In order to protect your health and inhibit the spread of Sars-Cov2, this year's iteration of IAM will be fully digital. We will use Microsoft Teams for communication and distributing lecture content. Regular teaching will begin on Friday, November 6, 2020, but you can already register for the course
and watch the introduction video.
02/10/2020 Website is online

Registration for this lecture was open until Friday, Nov 13. 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 published in the week before the tutorial takes place. It is not necessary to hand in the exercises and they will not be graded. All exercises are intended to be solved and discussed during the tutorial session in online group work. The lecturer will be available to assist you and check your solutions. 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 Tuesday, February 16, 2021 from 2:00 to 4:00 pm in Building E2.2, Günter Hotz Lecture Theatre.
The second written exam will take place on Monday, March 15, 2021 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.