bioRxivBiophysicsPreprint
SimpliPyTEM: An open-source Python library and app to simplify Transmission Electron Microscopy and in situ-TEM image analysis.
Abstract
Introducing SimpliPyTEM, a Python library and accompanying GUI that simplifies the post-acquisition evaluation of transmission electron microscopy (TEM) images, helping streamline the workflow. After an imaging session, a folder of image and/or video files, typically containing low contrast and large file size 32-bit images, can be quickly processed via SimpliPyTEM into high-quality, high-contrast .jpg images with suitably sized scale-bars. The app can also generate HTML or PDF files containing the processed images for easy viewing and sharing. Additionally, SimpliPyTEM has a specific focus on in situ TEM videos, an emerging field of EM, allowing for fast data processing into preview movies, averages, image series, or motion corrected averages using MotionCor2. The accompanying Python library offers many standard image processing methods, all simplified to a single command, plus a module to analyse particle morphology and population. This latter application is particularly useful for life sciences investigations. User-friendly tutorials and clear documentation are included to help guide users through the processing and analysis. We invite the EM community to contribute to and further develop this open-source package.
- assay: imaging
- assay: fluorescence / live-cell microscopy
- research focus: software / tool
- research focus: cell type annotation
- research focus: clustering
- research focus: dimensionality reduction
- approach: experimental assay
- approach: wet-lab / biochemical assay
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