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# System prepended metadata

title: webinar NEUBIAS

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# webinar NEUBIAS

## Outline

- 3 x ( 15 minutes presentation + 15 minutes Q&A ) ?!

## Tobias

- Big image data: Concepts and Challenges
    - Concepts:
        - caching
            and transparent access to cached images as if they would be in memory
        - multi-resolution representation
            for faster loading and fewer visualization artefacts
    - Challenges:
        - file formats
        - "cloud storage" -> there will be a separate webinar on this (?)
        - for visualization: intelligent caching, substitute resolution levels with already loaded data
        - for processing:
            - results storage
            - lazy evaluation
            - distributed computation
            - computation pipelines

- Introduction to BDV
    - Concepts: ViewerTransform => Physical Coordinate System => SourceTransform => Voxel Coordinate System => RealRandomAccessible (often: Voxels + Interpolator)
    - Viewing model relies on a physical coordinate system
        - One can show multiple images of different resolutions on top of each other
    - How to use it
- Why chunked multi-resolution image file formats are useful
    - Recommended community file-formats:
        - bdv.h5
        - bdv.n5
        - ome.zarr (to come)

## Nico

- BDV-playground
    - Bdv-BioFormats
        - Some commerical formats are also chunked multi-res (CZI, VSI, LIF)
        - Prepare your dataset for BDV applications - directly from the native image file formats
    - Navigate through your dataset and export it in ImageJ
    - Transfer easily between IJ1 and BigDataviewer (cropped regions)

## Tischi

- BigDataProcessor2
    - Open prevalent light-sheet and volume EM data formats in BigDataViewer.
    - Apply typical image pre-processing operations to TB sized image data, such as cropping, binning, chromatic shift and non-orthogonal acquisition correction.
    - Re-save the processed data for downstream image analysis.


## CONTENT SUMMARY

In this webinar, we will present concepts, challenges and solutions related to big image data. 
The presented solutions are part of the emerging FIJI BigDataViewer ecosystem.

The webinar is structured in four parts: a general introduction to the concepts of big image data, followed by a presentation of three tools. 

We first discuss the challenges of representing, storing, visualizing, and processing such data, and how these challenges are addressed in Fiji.
Second, we will demo the BigDataViewer user interface. This provides a basic way to interact with big images, multi-modal images, microscopy datasets with multiple angles or tiles, etc. 

A third part will be dedicated to easily opening, navigating and exporting your data thanks to a module called BigDataViewer-Playground. Multi-resolution support through Bio-Formats and BigDataViewer caching allow to navigate big 5D data without the need of converting files in most cases. BigDataViewer-Playground can thus be used as an entry point for other modules of the ecosystem such as BigStitcher, BigWarp, etc.

Finally, we will demonstrate BigDataProcessor2 (BDP2). With BDP2 you can open (TB sized) prevalent light-sheet and volume EM data formats and interactively apply typical image pre-processing operations such as cropping, binning, chromatic shift and non-orthogonal acquisition correction. The processed data can be re-saved for downstream image analysis.


