Analysing large-scale microscopy datasets with AI-based approaches
Project: Research
Research areas and keywords
UKÄ subject classification
- Basic Medicine
- Bioinformatics (Computational Biology)
- Mathematics
Keywords
- Machine Learning, Deep Learning, Microscopy, Computer Vision
Description
In this project we are developing AI-based approaches for analysing large datasets with microscopy images generated by high-content imaging screens.
| Status | Active |
|---|---|
| Effective start/end date | 2018/11/28 → … |
Collaborative partners
- Lund University (lead)
- National Bioinformatics Infrastructure Sweden, NBIS (Project partner)
- Science for Life Laboratory (SciLifeLab)
Participants
Related projects
(Predecessor)
Kalle Åström, Jacek Malec, Stefan Larsson, Mattias Ohlsson, Christian Balkenius, Anamaria Dutceac Segesten, Jutta Haider, Robert Willim, Jonas Ledendal, Jonas Wisbrant, Elin Anna Topp, Jörn Janneck, Marcus Klang, Einar Heiberg, Katja de Vries & Ingar Brinck
2018/01/01 → …
Project: Network
Sonja Aits, Kaylene Simpson, Ricky Johnstone, Nikolay Oskolkov & Charlotte Stadler
2016/12/01 → …
Project: Research
