Applied Machine Learning In Medical Imaging – Rene Donner

  Machine learning

Deep learning has had a great impact on Medical Imaging. But what is Medical Imaging? What are common Computer Vision tasks in that domain? We will look at registration, semantic segmentation, retrieval and anatomical structure localization. We will not only encounter DL techniques but also see the application of Random Forests, Random Ferns and Markov Random Fields. Lastly, we will look at publicly available data sets to get you started with Medical Imaging, as well as the practical aspects of working with medical domain experts.

With a background in electrical engineering, René has worked for 8 years at the Medical University Vienna as a researcher in computer vision, focussing on anatomical structure localization and content-based image retrieval. He is now CTO at contextflow, applying deep learning to large-scale medical image data and developing smart tools to aid radiologists in their challenging tasks.

Language: English

- Talk
- Discussion
- Networking (ImpactHub)

Machine Learning Meetups (MLMU) is an independent platform for people interested in Machine Learning, Information Retrieval, Natural Language Processing, Computer Vision, Pattern Recognition, Data Journalism, Artificial Intelligence, Agent Systems and all the related topics. MLMU is a regular community meeting usually consisting of a talk, a discussion and subsequent networking. At the end of the year 2016, MLMU also spread to Brno and Bratislava.