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bioRxiv · 10.1101/2025.02.27.640512

ProPicker: Promptable Segmentation for Particle Picking in CryogenicElectron Tomography

Wiedemann, S.·Fabian, Z.·Soltanolkotabi, M.·Heckel, R.
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Abstract

Cryogenic electron tomography (cryo-ET) produces detailed 3D images (tomograms) of cellular environments. A key step in cryo-ET data analysis is detecting all instances of a specific particle across tomograms (particle picking). This is a challenging object detection task due to strong noise, artefacts, and the crowded cellular context. Here, we propose ProPicker, a pretrained, promptable 3D segmentation model that enables a flexible and data-efficient particle picking workflow. By specifying a prompt, ProPicker is conditioned to detect a particle of interest and can then be used directly or can be fine-tuned to a particle-specific picker for improved accuracy. Experiments on simulated and real-world tomograms show that, using a single prompt, ProPicker achieves performance close to or on par with state-of-the-art methods while being up to an order of magnitude faster. Moreover, ProPicker can detect particles not seen during training. Fine-tuning ProPicker outperforms state-of-the-art particle-specific pickers if limited training data is available.

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Wiedemann, S., Fabian, Z., Soltanolkotabi, M., Heckel, R.. 2025-03-04. ProPicker: Promptable Segmentation for Particle Picking in CryogenicElectron Tomography. https://doi.org/10.1101/2025.02.27.640512

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