BAMresearch/automatic-sem-image-segmentation
Workflow for Simulation and Automatic Semantic Segmentation of Electron Microscopy Images
This project helps materials scientists and researchers automatically analyze electron microscopy images. It takes raw Scanning Electron Microscopy (SEM) or Transmission Electron Microscopy (TEM) images and outputs precise outlines or masks of agglomerated, non-spherical particles within them. This automation is designed for researchers who need to efficiently quantify and study complex particle structures.
Use this if you routinely analyze electron microscopy images and need to automatically identify and segment individual particles, especially those that are clustered or non-spherical.
Not ideal if your image analysis needs extend beyond particle segmentation in SEM/TEM images or if you require real-time, high-throughput processing on very large datasets without GPU acceleration.
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Last pushed
Feb 16, 2026
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