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| Semester | spring semester 2023 |
| Course frequency | Every spring sem. |
| Lecturers | Marcel Lüthi (marcel.luethi@unibas.ch, Assessor) |
| Content | Statistical shape models are models, which represent the typical variability of an organ or shape in terms of a probability distribution. The most important application of shape models is in medicine, where they are used for the analysis of medical images, surgery planning or the design of implants. There are, however, also many application in other fields, such as bio-mechanics, anthropology or forensics. In this course the participants will address a classical problem in the forensics sciences using shape modelling: Given a fragment of a bone, what can we say about the person? To solve this mystery, we will combine methods from mathematics, statistics and machine learning. More precisely, the participants will learn about Gaussian processes, Bayesian modelling and Markov Chain Monte Carlo methods. All the mathematical methods will be practically explored and visualized using the open source software library Scalismo. |
| Learning objectives | At the end of the course the students should be able to - describe how shapes can be analyzed using statistics . - apply the mathematical concept of a Gaussian process to model anatomical shapes - follow a principled Bayesian workflow for analysing shapes. - develop programs for medical image analysis using the open source software scalismo |
| Bibliography | Links to related literature will be given as part of the course. |
| Comments | Online course "Shape Modelling - Computing the human anatomy" available at https://shapemodelling.cs.unibas.ch/ssm-course/ |
| Weblink | Course Webpage |
| Admission requirements | Open to Master and PhD students with basic knowledge in probability theory and statistics, linear algebra as well as programming experience in a modern programming language (e.g. Java or C++) |
| Language of instruction | English |
| Use of digital media | Online, mandatory |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Tuesday | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Date | Time | Room |
|---|---|---|
| Tuesday 21.02.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 28.02.2023 | 14.15-16.00 | Fasnachstferien |
| Tuesday 07.03.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 14.03.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 21.03.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 28.03.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 04.04.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 11.04.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 18.04.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 25.04.2023 | 14.15-16.00 | Kollegienhaus, Seminarraum 103 |
| Tuesday 02.05.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 09.05.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 16.05.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 23.05.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Tuesday 30.05.2023 | 14.15-16.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 06.07.2023 | 14.00-16.00 | Alte Universität, Hörsaal -101 |
| Modules |
Doctorate Computer Science: Recommendations (PhD subject: Computer Science) Modul: Concepts of Machine Intelligence (Master's degree subject: Computer Science) Module: Applications of Distributed Systems (Master's Studies: Computer Science) Module: Methods of Machine Intelligence (Master's Studies: Computer Science) |
| Assessment format | continuous assessment |
| Assessment details | The final grade will be computed based on the result of a practical project and a written exam. The project contributes 50% and the written exam 50% to the final grade. Written exam, expected date: 6 July 2023, 2-4, Spiegelgasse 1, room 00.003. |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Fachbereich Informatik |