Speaker
Description
Deriving scientifically sound conclusions from microscopy experiments typically requires batch analysis of large image data sets. Once the analysis has been conducted it is critical to visually inspect the results to identify errors and to make scientific discoveries. Leveraging the ImgLib2/BigDataViewer ecosystem we developed a platform in which large image data sets can be conveniently inspected in a grid view mode. Each grid position contains one (multi-channel volumetric time-lapse) image and the corresponding segmentation results. All data are lazy loaded thereby supporting very large datasets. This image grid view is linked with a table view and a scatterplot view, in which measurements of segmented objects can be inspected. Objects can be highlighted, coloured, annotated and selected in all views. All functionality is easily accessible via the MoBIE update site of Fiji.
In this workshop, we will demonstrate how to this generic framework can be used for batch inspection of data produced with Fiji, Cellprofiler, ilastik, and Nextflow managed python scripts.
| Target audience | Intermediate users |
|---|---|
| Keywords | Batch analysis, ImgLib2, BigDataViewer, Fiji, Quality Control |
