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53822-01 - Vorlesung: Advanced Methods in Medical Image Analysis (3 KP)
| Semester | Frühjahrsemester 2024 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende |
Florentin Bieder (florentin.bieder@unibas.ch)
Philippe Claude Cattin (philippe.cattin@unibas.ch, BeurteilerIn) Julia Wolleb (julia.wolleb@unibas.ch) |
| Inhalt | This course provides an introduction to deep learning and how this cutting-edge technology can be applied to medical image analysis. The course covers the following topics • Fundamentals of deep learning • Numerical optimization (for training machine learning models) • Multilayer perceptrons • Convolutional Neural Networks (CNNs) and their medical applications • Segmentation with CNNs • Autoencoders • Generative models • Deep learning models for sequential data |
| Lernziele | • Understand the basics of deep learning and how it can be applied to medical image analysis • Understand numerical optimization algorithms used to train deep learning models • Understand the architecture and training of multilayer perceptrons and CNNs • Medical applications of MLPs and CNNs for classification, regression, segmentation, and anomaly detection tasks • Know different generative models and their medical applications • Know appropriate models for sequential data analysis |
| Weblink | DBE MA BME |
| Teilnahmevoraussetzungen | (C15) Medical Imaging and Medical Image Processing; Python Knowledge similar to course 69472 Limited student numbers, priority given to student in Biomedical Engineering |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Mittwoch | 15.15-17.00 | Hegenheimermattweg 167B, Lecture Hall 02. 097 |
Einzeltermine
| Module |
Modul: Biomedical Engineering Electives (Masterstudium: Biomedical Engineering) Modul: Electives in Data Science (Masterstudium: Data Science) Modul: Image-Guided Therapy (Masterstudium: Biomedical Engineering (Studienbeginn vor 01.08.2023)) Modul: Vertiefung Medizinische Nanowissenschaften (Masterstudium: Nanowissenschaften) |
| Prüfung | Leistungsnachweis |
| Hinweise zur Prüfung | written exam |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | eine Wiederholung, bester Versuch zählt |
| Skala | 1-6 0,1 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Medizinische Fakultät |
| Anbietende Organisationseinheit | Departement Biomedical Engineering (DBE) |