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Research:

As researchers, we develop advanced methods and software tools to quantify and mine the rich information present in microscopy images, increasing the scientific value of biomedical experiments based on image data. Our past and ongoing research projects are best reflected by our publications.
Our two largest, externally funded projects are
• the ERC funded TissueMaps project
• the SSF funded HASTE project

Ongoing projects during 2016 are listed in the CBA 2016 Annual Report.

Support:



We provide research support and education via the BioImagInformatics (BIIF) facility of SciLifeLab. We develop computational methods that automatically analyze and understand images of biological processes, using microscopic images as their primary source of information. We draw upon methods from computer vision, machine learning, statistics, and bioinformatics to quantify image data and answer biological questions. We do not primarily analyze data for our facility users, but rather help users get started with their own analysis. We find that projects work best when researchers are closely involved in the analysis of their own data. The SciLifeLab BioImage Informatics Facility is headed by Petter Ranefall, and has two nodes; one in Stockholm, connected to the School of Computer Science and Communication at KTH directed by Kevin Smith, and one in Uppsala, at the Centre for Image Analysis, Dept. of Information Technology directed by Carolina Wählby, Uppsala University.

Past teaching activities are listed here while upcoming activities are announced on the BioImagInformatics (BIIF) facility page. Apart from our own algorithm development, we work closely with developers of free and open-source CellProfiler software. We have created our own educational material located here.