Okapi-EM: A napari plugin for processing and analyzing cryogenic serial focused ion beam/scanning electron microscopy images.
Luís M A PerdigãoElaine M L HoZhiyuan C ChengNeville B Y YeeThomas GlenLiang WuMichael GrangeMaud DumouxMark BashamMichele C DarrowPublished in: Biological imaging (2023)
An emergent volume electron microscopy 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 visualization 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 article presents Okapi-EM, an open-source napari plugin developed to process and analyze cryogenic serial pFIB/SEM images. Okapi-EM enables automated image registration of slices, evaluation of image quality metrics specific to pFIB-SEM imaging, and mitigation of charging artifacts. 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.
Keyphrases
- electron microscopy
- deep learning
- convolutional neural network
- image quality
- artificial intelligence
- optical coherence tomography
- machine learning
- high resolution
- climate change
- healthcare
- single molecule
- magnetic resonance imaging
- electronic health record
- quality improvement
- mass spectrometry
- low cost
- liver fibrosis