2021-10-18

HT2021, 1.5 ECTS or 6 ECTS

Objectives

Artificial intelligence (AI) can be used for state-of-the art image analysis and generation in medicine and life sciences in a variety of contexts, e.g. to find tumors in MRIs, detect skin cancers, quantify different cell types in microscopy images, measure animal behaviour in vidoes or generate artificial training data.

This course will introduce students to image and video analysis with deep learning and application areas within medicine and life sciences. It is also suitable for people outside the medicine/life science area as the concepts and methods themselves are not specific to this domain. The course will cover typical image analysis tasks that can be solved by deep learning models, e.g. classification, object detection, segmentation and image generation and practical applications of this. It will also go through the basic building blocks of deep learning models, typical architectures used for image analysis tasks and the steps required to train and evaluate models.

The course will mix lectures, hands-on computational exercises, Q and A sessions and research-related parts.

The first part of the course will be taught as a block, which counts as 1.5 ECTS. It is possible to extend this with a 4.5 ECTS optional project work over three weeks following the first block.

Dates

18, 19, 22, 25 an 26 October (for the 1.5 ECTS block). If you are unable to attend all days, you may still be able to participate in the course.

Optional project work until 17 November, required for additional 4.5 ECTS.

All teaching will be online.

Personnel

Course organiser: Sonja Aits

Teachers: Sonja Aits, Marcus Klang

Pre-requisite/requirements

• Basic programming skills in Python
• Basic understanding of AI concepts (e.g. COMPUTE course "Artificial Inteligence in Medicine and Life Science - Introduction", NTF014F or equivalent self studies)
• Standard computer/laptop with internet connection

If you lack the pre-requisites self-study material prior to the course can be provided. No prior knowledge in medicine and life science is required to take part in the course.

It is typically not possible to admit MSc students to COMPUTE courses.

Registration

Registration is now closed.

Registration closes: 10th October 2021 (firm)