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| Semester | spring semester 2024 |
| Course frequency | Every spring sem. |
| Lecturers |
Florentin Bieder (florentin.bieder@unibas.ch)
Philippe Claude Cattin (philippe.cattin@unibas.ch, Assessor) Julia Wolleb (julia.wolleb@unibas.ch) |
| Content | 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 |
| Learning objectives | • 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 |
| Admission requirements | (C15) Medical Imaging and Medical Image Processing; Python Knowledge similar to course 69472 Limited student numbers, priority given to student in Biomedical Engineering |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Wednesday | 15.15-17.00 | Hegenheimermattweg 167B, Lecture Hall 02. 097 |
| Modules |
Modul: Biomedical Engineering Electives (Master's Studies: Biomedical Engineering) Module Specialisation: Medical Nanosciences (Master's Studies: Nanosciences) Module: Electives in Data Science (Master's Studies: Data Science) Module: Image-Guided Therapy (Master's Studies: Biomedical Engineering (Start of studies before 01.08.2023)) |
| Assessment format | record of achievement |
| Assessment details | written exam |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | one repetition, best attempt counts |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Medicine |
| Offered by | Departement Biomedical Engineering (DBE) |