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CryoTriage

Automated cryo-EM micrograph quality control. 2D astigmatic CTF fit (defocus, astigmatism, resolution), ice & drift detection, and a PASS / FLAG / REJECT verdict — first-principles, CPU-only, no RELION or cryoSPARC required.

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Who it's for

Cryo-EM facility staff, microscope operators screening grids live, and labs curating micrographs before reconstruction.

Why it helps

Catch bad micrographs — thick ice, drift, off-target defocus, contamination — before they waste GPU hours on a reconstruction.

How it's different

Transparent, first-principles CTF fit (CTFFIND4-comparable). No GPU, no model weights, every threshold inspectable. Validated to 5.1 Å mean defocus error on EMPIAR data.

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Drop a micrograph here, or click to choose

.mrc · .tif/.tiff · .png/.jpg — a motion-corrected micrograph or single frame

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See the example report, browse the source on GitHub, or run it locally: python cryotriage.py triage your_micrographs/

First-principles CTF estimation following Rohou & Grigorieff (2015), no CTFFIND/RELION binary required. Validated on synthetic known-defocus data (5.1 Å mean error) and real EMPIAR-10025 / 10061 micrographs. Large .mrc files are downsampled for QC. Your micrograph is processed in-memory to produce the report and is not stored or uploaded permanently.
github.com/gianyrox/cryotriage