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. 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. Here we describe GIANI (djpbarry.github.io/Giani), new software for the analysis of 3D images, implemented as a plugin for the popular FIJI platform. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images and also comes with scripting and command line tools, allowing users to incorporate its functionality into their own scripts and also run GIANI on a high-performance computing cluster. 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. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.

中文翻译：

---

GIANI：用于自动分析 3D 显微图像的开源软件

对生理相关三维 (3D) 系统中细胞和发育过程的研究有助于理解细胞命运、疾病和损伤的潜在机制。虽然尖端显微镜技术允许常规获取 3D 数据集，但目前用于分析此类图像的开源软件包数量有限。在这里，我们描述了 GIANI (djpbarry.github.io/Giani)，这是一种用于分析 3D 图像的新软件，作为流行的 FIJI 平台的插件实现。该设计主要有利于细胞核和细胞的分割，然后是形态和蛋白质表达的量化。GIANI 支持对大量图像进行常规和可重复的批处理，还附带脚本和命令行工具，允许用户将其功能合并到自己的脚本中，并在高性能计算集群上运行 GIANI。我们通过量化小鼠早期胚胎共聚焦图像中的细胞形态和蛋白质表达以及从面粉甲虫胚胎的光片显微镜图像中分割细胞核来证明 GIANI 的效用。我们还使用模拟数据验证了软件的性能。更一般地说，我们预计 GIANI 将成为各种生物医学领域研究人员的有用工具。我们还使用模拟数据验证了软件的性能。更一般地说，我们预计 GIANI 将成为各种生物医学领域研究人员的有用工具。我们还使用模拟数据验证了软件的性能。更一般地说，我们预计 GIANI 将成为各种生物医学领域研究人员的有用工具。