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43075-01 - Vorlesung: Probabilistic Shape Modelling 6 KP

Semester Frühjahrsemester 2019
Angebotsmuster Jedes Frühjahrsem.
Dozierende Marcel Lüthi (marcel.luethi@unibas.ch, BeurteilerIn)
Inhalt Statistical shape models are one of the most important technologies in computer vision and medical image analysis. With this technology, the computer learns the characteristic shape variations of an object or organ. The model resulting from this analysis may then be used in implant design, image analysis, surgery planning and many other fields.

In this course, you will get insights from mathematics, statistics and machine learning, in order to address practical problems, as well as a theoretical and practical introduction to the open source software Scalismo. This software is used today for the automatic detection of organs in medical images or the design of medical implants. You will come to a point where you can use your acquired skills and knowledge for real-world professional applications or academic research.
Lernziele At the end of the course the students should be able to
- describe how medical images can be analysed using Shape models.
- apply the mathematical concept of a Gaussian process to model anatomical shapes
- understand Bayesian approaches to medical image analysis
- to develop programs for medical image analysis using the open source software scalismo
Literatur Links to related literature will be given as part of the online course.
Bemerkungen Requires participation in the online course "Shape Modelling - Computing the human anatomy" (www.futurelearn.com/courses/statistical-shape-modelling)

 

Teilnahmebedingungen 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++)
Unterrichtssprache Englisch
Weblink Course Webpage, online course
Einsatz digitaler Medien Online-Angebot obligatorisch
HörerInnen willkommen

 

Intervall wöchentlich
Datum 19.02.2019 – 28.05.2019
Zeit Dienstag, 14.15-16.00 Spiegelgasse 5, Seminarraum 05.002
Datum Zeit Raum
Dienstag 19.02.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 26.02.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 05.03.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 12.03.2019 14.15-16.00 Uhr Fasnachtsferien
Dienstag 19.03.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 26.03.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 02.04.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 09.04.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 16.04.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 23.04.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 30.04.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 07.05.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 14.05.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 21.05.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Dienstag 28.05.2019 14.15-16.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Module Doktorat Informatik: Empfehlungen (Promotionsfach Informatik)
Modul Applications of Distributed Systems (Master Computer Science)
Modul Concepts of Machine Intelligence (Master Studienfach Computer Science)
Modul Methods of Machine Intelligence (Master Computer Science)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung The final grade will be computed based on the result of 2 practical projects and an oral exam.
Each project contributes 25% to the final grade and the oral exam 50%.
An-/Abmeldung zur Leistungsüberprüfung An-/Abmelden: Belegen resp. Stornieren der Belegung via MOnA
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,5
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch
Anbietende Organisationseinheit Fachbereich Informatik

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