![]() In cases where 3D datasets are supported, analyses can be challenging to execute for novice users, potentially requiring a complex combination of commands from multiple plugins. However, their support for 3D analysis is often limited – for example, several CellProfiler ( Lamprecht et al., 2007) modules are not yet compatible with 3D images. There are numerous excellent, freely available bioimage analysis tools in the open source domain. Furthermore, the closed-source nature of such software prevents detailed interrogation of specific calculations and processes. However, licences for such software are expensive and they also rely on proprietary file formats. ![]() Commercial packages, such as Imaris (Bitplane) and Vison4D (Arivis) provide excellent visualisation functionality and are also equipped with analysis tools. Manual annotation of such data is not feasible in a reasonable time frame. However, the development of software for the quantitative analysis of such data has not kept pace with imaging advances, and there is now a pressing need for automated solutions ( Meijering et al., 2016). ![]() Commonly used 3D culture formats include, but are not limited to, populations of single cells in organotypic matrices, spheroid models, tissue sections or whole embryos and organisms. There has long been an acceptance that two-dimensional (2D) cell cultures might not accurately recreate behaviours found in complex three-dimensional (3D) in vivo environments ( Duval et al., 2017). The ability to routinely acquire multi-dimensional datasets with modern microscopy techniques is transforming, among other fields, cell biology, developmental biology and cancer research. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields. We also validate the performance of the software using simulated data. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light-sheet microscopy images of the flour beetle embryo. GIANI enables routine and reproducible batch-processing of large numbers of images, and comes with scripting and command line tools. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. Here, we describe General Image Analysis of Nuclei-based Images (GIANI ), new software for the analysis of 3D images. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. The study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury.
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