Okapi-EM - a napari plugin for processing and analysing cryogenic serial FIB/SEM images

An emergent volume electron microscopy (vEM) technique called cryogenic serial plasma focused ion beam milling scanning electron microscopy (pFIB/SEM) can decipher complex biological structures by building a three-dimensional picture of biological samples at mesoscale resolution. This is achieved by collecting consecutive SEM images after successive rounds of FIB milling that expose a new surface after each milling step. Due to instrumental limitations, some image processing is necessary before 3D visualisation and analysis of the data is possible. SEM images are affected by noise, drift, and charging effects, that can make precise 3D reconstruction of biological features difficult. This paper presents Okapi-EM, an open-source Napari plugin(1) developed to process and analyse cryogenic serial FIB/SEM images. Okapi-EM enables automated image registration of slices, evaluation of image quality metrics specific to FIB-SEM imaging, and mitigation of charging artefacts. Implementation of Okapi-EM within the Napari framework ensures that the tools are both user- and developer-friendly, through provision of a graphical user interface and access to Python programming. Napari also hosts a variety of other image processing plugins so Okapi-EM tools can be integrated into and combined with other workflows. Okapi-EM can be downloaded freely at https://github.com/rosalindfranklininstitute/okapi-em, or installed from Python package index (PyPI). Impact statementCryogenic serial pFIB/SEM is an emerging microscopy technique that is used to visualise 3D structures of biological features at mesoscale resolutions(2). This technique requires common post processing of data such as alignment and charge mitigation to enable robust segmentation and analysis. In addition, approaches are needed to quantify data quality to enable an assessment of features and tune data acquisition parameters to enable optimal image acquisition. This article presents Okapi-EM, a combination of software tools designed to facilitate these important initial steps in assessing and processing images from these experiments. These tools have been assembled as a plugin for a popular 3D biological image visualiser called Napari, making their usage user-friendly and readily accessible.