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| Biomedical Signal and Image Processing |
| Lecturer: |
| Prof. Dr. rer. nat. Dagmar Krefting, apl. Prof. Christian Dullin, Dr. Philip Hempel, Tabea Friederike Agnes Steinbrinker, Christoph Jensen |
| Course typ: |
| Seminar |
| Description: |
| Learning objectives The students • name and describe aims and typical tasks in biomedical signal and image processing. • name the relevant signal and imaging techniques in biomedicine and explain their essential characteristics. • describe essential mathematical and physical contexts – on an appropriate level - which are the basis for the introduced techniques. • explain concepts overarching the fields of signal and image processing, e.g. signal-to-noise ratio, sampling, quantization, system theory. explain the fundamentals of signal and image processing in time, frequency and time-frequency domain. • explain typical use-cases, e.g. signal delineation and image segmentation, and explain encountered challenges explain fundamentals of multiscale signal and image analysis. • apply each of the theoretical fundamentals in practical use cases with established software tools. Content keywords Electrical biosignals in biomedicine and their digital representation; typical processing chain starting with signal acquisition, followed by filtering and feature extraction; sampling theorem, aliasing; Linear-time invariant systems and their properties; Time and frequency domain representations of signals, uncertainty principle on time-frequency transforms: Short-time Fourier Transform, Discrete Wavelet Transform, Continuous Wavelet Transform; Convolution Theorem. Radiological, nuclear-medicine, and optical procedures in medicine; digital image representation, processing chain, resolution and contrast, contrast enhancement, noise reduction, filter techniques; detection of points, lines, edges, and segments, threshold and area-oriented operations, feature extraction. Use of tools such as Python, Numpy, Scipy, Matplotlib. |
| Place: |
| (Seminar Room 01.C.139 in Von-Siebold-Strasse 3): Fri.. 09:00 - 11:00 (10x) Tuesday, 11.11.2025 13:00 - 15:00, Tuesday, 11.11.2025 15:30 - 17:00, Wednesday, 19.11.2025, Wednesday, 03.12.2025 14:00 - 16:00, Thursday, 08.01.2026 12:15 - 13:45, Wednesday, 21.01.2026 14:00 - 17:00, Thursday, 22.01.2026 12:15 - 13:45, Tuesday, 27.01.2026, Tuesday, 03.02.2026 14:00 - 16:00, (Meeting at Elevator Shaft C1 on Level 0 in Hospital Main Building): Fri.. 09:00 - 11:00 (1x), (Heart and Brain Center, Seminar Room 2.126/2.130): Monday, 03.11.2025 13:00 - 15:00, (HS Med 24 (Kreuzbergring/Von-Siebold-Straße)): Wednesday, 18.02.2026 10:00 - 12:00 |
| Semester: |
| WiSe 2025/26 |
| Times: |
| Fri.. 09:00 - 11:00 (weekly),
Dates on Monday, 03.11.2025, Tuesday, 11.11.2025 13:00 - 15:00, Tuesday, 11.11.2025 15:30 - 17:00, Wednesday, 19.11.2025, Wednesday, 03.12.2025 14:00 - 16:00, Thursday, 08.01.2026 12:15 - 13:45, Wednesday, 21.01.2026 14:00 - 17:00, Thursday, 22.01.2026 12:15 - 13:45, Tuesday, 27.01.2026, Tuesday, 03.02.2026 14:00 - 16:00, Wednesday, 18.02.2026 10:00 - 12:00 First appointment: Monday, 03.11.2025 13:00 - 15:00, Room: (Heart and Brain Center, Seminar Room 2.126/2.130) |
| Course number: |
| M.Inf.1309 |
| Participants: |
| Students in the master study program applied computer science. Students in the master study program applied data science. Elective module for students of physics and mathematics. Students from other faculties/ study programs are kindly asked to contact teaching coordination office: mi-lehre@med.uni-goettingen.de |
| Learning organisation: |
| The module is taught in English. |
| Performance accreditation: |
| Module Exam M.Inf.1309: Biomedical Signal and Image Processing. The exam type is a practical exam ("praktische Prüfung"). It consists of regular, weekly assignments (80%) and a final project and presentation of results (ca. 30 min.) (20%) in the seminar. By means of a practical examination, the students continuously work on programming assignments that form a larger seminar project. The practical examination can be conducted in groups. The regular assignment results have to be submitted, and presented in the seminar. Grading criteria will be presented to the students at the start of the module. Detailed requirements are incorporated in the assignments. |
| Area classification: |
| Vorlesungsverzeichnis WiSe 2025/26 |
| ECTS credit points: |
| 6 |
| Further information from Stud.IP about this course |
| Home institute: Institut für Medizinische Informatik Participants registered in Stud.IP: 14 Number of postings in Stud.IP forum: 14 Number of documents in the Stud.IP download area: 52 |