This Micro-Module is structured into introduction, self-learning, and implementation phases. First, you will get input on recent feature extraction and data analysis methods. You will work in a small team of three to four students solving detection and classification tasks on medical image data. In particular, your task is to automatically detect surgical tools and their motion in endoscopic images. To tune and test your algorithms we will provide image data from a surgical daVinci imaging system acquired in our laboratory. Participating in image annotation also allows you to better understand AI models and their limitations. Finally, we will test your algorithms on real medical image data. You can compare your results directly with other groups through our online leaderboard.
Image Analysis for Intelligent Systems in Medicine
Image Analysis for Intelligent Systems in Medicine
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Description
AI is becoming an increasingly important tool for clinical tasks, e.g., medical image processing or decision making. In this course you will have the opportunity to learn the fundamentals of different AI methods and apply these methods practically to real clinical image data. We will provide datasets - acquired partially in our laboratory – to train models on detection and classification tasks for surgical image analysis. You will work in an interdisciplinary and international team on this project.
The Team
- Topics
- Study format
- Hybrid
- Application period
- 1 September – 11 October 2024
- Study period
- 1 November 2024 – 23 January 2025
- Credits
- 2 ECTS
- Pace
- 20%
- Hosting university
- Hamburg University of Technology
Learning outcomes
Gain practical experiences in medical image analysis
At the end of the course learner will gained a practical experiences in acquiring, pre-processing and analyzing medical image data.
ESCO SKILLS
Implement data analysis algotithm
At the end of the course the learner is able to implement data analysis algotithm using principles of artificial intelligence.
ESCO SKILLS
Organize Coding in a team
At the end of the course learners solved coding taks successfully in a team and forster their skills in collaborative problem-solving.
ESCO SKILLS
Potential progress
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Information
This Micro-Module is structured into introduction, self-learning, and implementation phases. First, you will get input on recent feature extraction and data analysis methods. You will work in a small team of three to four students solving detection and classification tasks on medical image data. In particular, your task is to automatically detect surgical tools and their motion in endoscopic images. To tune and test your algorithms we will provide image data from a surgical daVinci imaging system acquired in our laboratory. Participating in image annotation also allows you to better understand AI models and their limitations. Finally, we will test your algorithms on real medical image data. You can compare your results directly with other groups through our online leaderboard.
Hosting university
Hamburg University of Technology
