Light-Sheet Image Reconstruction and Analysis
Light-sheet microscopy is an emerging technology that currently transforms developmental biology, enabling imaging of developing specimen such as Drosophila or mouse embryos with a spatiotemporal resolution that has the potential to follow every individual throughout the entire development. In different configurations, light-sheet microscopy also allows imaging of large fixed or expanded tissues, like entire mouse brains at single-cell resolution. While image acquisitions are now possible even using commercial microscopes, the image datasets typically amount to terabytes of data that pose huge challenges for image reconstruction and analysis necessary to extract useful data.
Directed by Stephan Preibisch, Stephan Saalfeld and Philipp Keller, this bootcamp course will train scientists on existing open-source solutions for the reconstruction and analysis of light-sheet microscopy datasets. This includes strategies for image storage, handling, alignment, deconvolution, visualization, as well as segmentation and tracking. The training will be performed on state-of-the-art light-sheet microscopy datasets acquired in the Keller lab, but participants will have sufficient time to apply it to their own dataset they are encouraged to bring along.
This course is designed for scientists at all career stages that either plan to use light-sheet microscopy for their research, or struggle with already existing acquisitions that they plan to reconstruct and analyze. Priority will be given to applicants who illustrate a clear need for light-sheet microscopy for their research goals.
To maintain the small group atmosphere, space in the workshop is limited, and participants are expected to stay for the duration. We encourage applications from individuals with diverse backgrounds.
Janelia will cover the cost of accommodation and meals. Travel expenses are not covered, but support is available for those in need. Participants are expected to attend for the duration.
To be considered, applicants must apply online and provide:
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