IAFIG-RMS: Bioimage analysis with Python
Organizer: University of Cambridge
Host institution: University of Cambridge Bioinformatics Training
Start: Monday, 09 December 2019 @ 09:30
End: Friday, 13 December 2019 @ 17:00
Venue: Craik-Marshall Building
Country: United Kingdom
Postcode: CB2 3AR
Scientific topic: Data visualisation, Data mining, Biological imaging, BioinformaticsTarget audience:
- Cell Biologists
- BioImage Analysts with some experience of basic microscopy image analysis
- This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis
- This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.
- The course is open to Graduate students
- Postdocs and Staff members from the University of Cambridge
- Institutions and other external Institutions or individuals
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Members of Industry to pay 575.00 GBP. </span style> <span style="color:#0000FF">All Members of the University of Cambridge
- Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>
THIS EVENT IS NOW FULLY BOOKED!
The aim of this 5 days course is to develop motivated participants toward becoming independent BioImage Analysts in an imaging facility or research role. Participants will be taught theory and algorithms relating to bioimage analysis using Python as the primary coding language.
Lectures will focus on image analysis theory and applications. Topics to be covered include: Image Analysis and image processing, Python and Jupyter notebooks, Visualisation, Fiji to Python, Segmentation, Omero and Python, Image Registration, Colocalisation, Time-series analysis, Tracking, Machine Learning, and Applied Machine Learning.
The bulk of the practical work will focus on Python and how to code algorithms and handle data using Python. Fiji will be used as a tool to facilitate image analysis. Omero will be described and used for some interactive coding challenges.
Research spotlight talks will demonstrate research of instructors/scientists using taught techniques in the wild.
The training room is located on the first floor and there is currently no wheelchair or level access available to this level.
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