3D microscopy images are used in the field of cell and developmental biology predominantly to quantitatively analyze embryonic phenotypes. Integrating 3D imaging data from a multitude of biological samples, such as whole-mount embryos is challenging due to significant variations in size and accurate imaging orientation among individual embryos.

In collaboration with the group of Martin Burger ( https://en.www.math.fau.de/angewandte-mathematik-1/ ) we developed Landscape – a user-friendly “all-in-one” image processing and analysis software platform which allows integrating and registering 3D imaging data derived from a large number of biological samples, thereby facilitating detailed and quantitative investigation of variable biological phenotypes in different ellipsoidal organisms, such as zebrafish and Drosophila embryos.
( https://advances.sciencemag.org/content/6/49/eabc5546 ).

The Landscape software can be employed to address various questions in developmental and cell biology. For example, the quantitative analysis of expression patterns in whole-mount embryos (e.g., in situ hybridization) and staining of histological tissue sections could benefit from the software. Specifically, in contrast to manual assessments of individual embryos or sections, Landscape allows pooling and comparing large amount of data sets for non-biased quantitative analysis that could reveal phenotypes that could not be observed when evaluating single datasets.

Landscape automatically processes and registers the 3D imaging data in multiple interdependent steps (see workflow below). Embryos are normalized, registered with respect to size and orientation, and overlayed. To visualize the 3D data, similar to the earth’s projection onto cartographic maps, the 3D data derived from the imaged embryos are unfolded to generate 2D projection maps.