ZELDA: A 3D Image Segmentation and Parent-Child Relation Plugin for Microscopy Image Analysis in napari - D’Antuono, Rocco; Pisignano, Giuseppina (Frontiers in Computer Science, 2022)
Bioimage analysis workflows allow the measurement of sample properties such as fluorescence intensity and polarization, cell number, and vesicles distribution, but often require the integration of multiple software tools. Furthermore, it is increasingly appreciated that to overcome the limitations of the 2D-view-based image analysis approaches and to correctly understand and interpret biological processes, a 3D segmentation of microscopy data sets becomes imperative. Despite the availability of numerous algorithms for the 2D and 3D segmentation, the latter still offers some challenges for the end-users, who often do not have either an extensive knowledge of the existing software or coding skills to link the output of multiple tools. While several commercial packages are available on the market, fewer are the open-source solutions able to execute a complete 3D analysis workflow. Here we present ZELDA, a new napari plugin that easily integrates the cutting-edge solutions offered by python ecosystem, such as scikit-image for image segmentation, matplotlib for data visualization, and napari multi-dimensional image viewer for 3D rendering. This plugin aims to provide interactive and zero-scripting customizable workflows for cell segmentation, vesicles counting, parent-child relation between objects, signal quantification, and results presentation; all included in the same open-source napari viewer, and “few clicks away”.