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53822-01 - Lecture: Advanced Methods in Medical Image Analysis (3 CP)

Semester spring semester 2025
Course frequency Every spring sem.
Lecturers Florentin Bieder (florentin.bieder@unibas.ch)
Philippe Claude Cattin (philippe.cattin@unibas.ch, Assessor)
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

Dates

Date Time Room
Wednesday 19.02.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 26.02.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 05.03.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 12.03.2025 15.15-17.00 Fasnachstferien
Wednesday 19.03.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 26.03.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 02.04.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 09.04.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 16.04.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 23.04.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 30.04.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 07.05.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 14.05.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 21.05.2025 15.15-17.00 Hegenheimermattweg 167B, Lecture Hall 02. 097
Wednesday 28.05.2025 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)
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)

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