Abstract
AbstractThe implementation of computational tools for analysis of microscopy images has been one of the most important technological innovations in biology, providing researchers unmatched capabilities to comprehend cell shape and connectivity. Most available tools frequently focus either on segmentation or morphological analysis, thus not providing an inclusive pipeline. We introduce CellWalker, a computational pipeline that streamlines and connects the segmentation step with the morphological analysis in a modular manner. This python-based pipeline starts with ‘visible-source’ IPython notebooks for segmentation of 2D/3D microscopy images using deep learning and visualization of the segmented images. The next module of CellWalker runs inside Blender, an open-source computer graphics software. This addon provides several morphometric analysis tools that can be used to calculate distances, volume, surface areas and to determine cross-sectional properties. It also includes tools to build skeletons, calculate distributions of sub-cellular organelles. Overall, CellWalker provides practical tools for segmentation and morphological analysis of microscopy images in the form of an open-source and modular pipeline which allows a complete access to fine-tuning of algorithms through visible source code while still retaining a result-oriented interface.Contactharshkhare@gmail.com,chiara.zurzolo@pasteur.frAvailability and implementationCellWalker source code is available on GitHub (https://github.com/utraf-pasteur-institute/CellWalker-notebooksandhttps://github.com/utraf-pasteur-institute/CellWalker-blender) under a GPL-3 license.
Publisher
Cold Spring Harbor Laboratory