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PickyMate: Interactive & Iterative Curation of Cryo-Electron Tomography Template Matching Annotations Using Pretrained Model Embeddings

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PickyMate

Interactive curation of particles picked in cryo-electron tomograms.

Template matching (or any picker) finds your particles, but it over-picks: thousands of hits, most of them junk. PickyMate turns cleaning that list from a one-by-one slog into a few rounds of bulk decisions. Every pick carries a foundation-model embedding (TomoTwin, CryoSIAM); as you confirm good particles and reject junk, PickyMate re-ranks everything else by similarity to your own decisions — live, while you work — so lookalikes of what you confirmed come to you and lookalikes of what you rejected sink away. The same works across a whole dataset: decisions made in the tomograms you have finished re-rank the ones you have not opened yet.

What PickyMate does

The moment that matters, live from the app — you confirm a few good particles, and one click reorders thousands of picks around them:

Ranking, animated

Everything can also be fixed by hand — three orthogonal slice views, click to add or remove a pick, organize into sets, all saved as plain x y z text files. But start from the template-matching list: only its picks carry embeddings, so a particle picked by hand cannot take part in the ranking.

Install

With conda (creates a pickymate environment with the pickymate command):

git clone https://github.com/Image-Analysis-Hub/PickyMate.git
cd PickyMate
conda env create -f environment.yml
conda activate pickymate

Into an environment you already have — editable from a clone, or straight from GitHub:

pip install -e .                # from inside the clone; edits take effect immediately
pip install git+https://github.com/Image-Analysis-Hub/PickyMate.git

Run

pickymate tomogram.mrc                 # one tomogram
pickymate --session session.csv        # a whole dataset

Documentation

docs/ — a short, searchable user guide:

About

PickyMate: Interactive & Iterative Curation of Cryo-Electron Tomography Template Matching Annotations Using Pretrained Model Embeddings

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