Overordnede kursusmål
Biomedical image analysis is a broad topic that covers a variety of
disciplines in modern computer science, AI Research, medical
sciences and biology. In this summer school, we aim at given the
participant a good overview of the current state-of-the-art in
several of the fundamental topics used in modern biomedical image
analysis.
Læringsmål
En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:
- Describe the main ways of biomedical image acquisition
- Import and visualize large 3D data sets using Python
- Describe and evaluate state-of-the-art 3D high-energy scanning
approaches
- Do basic analysis of human motion data
- Describe and evaluate the use of motion tracking systems for 3D
image corrections
- Implement and use implicit methods for 3D data
representations
- Describe and use different parameterizations of complex 3D
shapes
- Describe the concept of fairness and bias in relation to
medical image analysis
- Implement and use a selection of methods for 2D and 3D
structural analysis
Kursusindhold
Biomedical image analysis typically starts with the acquisition of
data. This can for example be large 3D volume data from high-energy
scanners, human motion data from optical or infrared sensors, cell
images from microscopes or standard historical photos of species.
We have invited a group of speakers that are specialist in several
of these techniques.
A common issue with complex data is how to represent the data in a
compact way but where the information is still preserved.
Currently, there is a large research interest in implicit
representation of 3D shapes for machine learning. These
representation and other suitable ways of handling complex
biomedical data is also presented at the summer school.
While much modern image analysis is based on large deep neural
networks, there is still a need for knowing about core methods like
advanced 3D morphological analysis and statistics of shapes. There
will be expert speakers in this field.
With the modern data driven approaches it can be very hard to judge
the fairness and biases of the models. We will have a session on
these complex topic.
The course will include group based project work, where the
participants make a programming project relating their research to
the summer school’s topics. It will be in the form of a challenge.
Litteraturhenvisninger
Please see the homepage:
https://biomed.compute.dtu.dk/talks-materials-and-exercises/Bemærkninger
In order to participate in the course, you need to register on the
homepage and pay the participation fee:
https://biomed.compute.dtu.dk/Sidst opdateret
19. marts, 2024