Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Electron Microscope Tomography and Single-particle Reconstruction

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Magnetocardiography to screen adults with arrhythmogenic cardiomyopathy: A feasibility study.

American heart journal plus : cardiology research and practice·2026

Same author

Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction.

IEEE transactions on information theory·2026

Same author

Hyperphantasia: A Benchmark for Evaluating the Mental Visualization Capabilities of Multimodal LLMs.

Advances in neural information processing systems·2026

Same author

The Rich and the Simple: On the Implicit Bias of Adam and SGD.

Advances in neural information processing systems·2026

Same author

Emergence and Evolution of Interpretable Concepts in Diffusion Models.

Advances in neural information processing systems·2026

Same author

MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI.

ArXiv·2026

Same journal

Ultrastructural evidence of autophagy-related processes and mitochondrial remodeling in the myxozoan parasite Henneguya piaractus.

Journal of structural biology·2026

Same journal

Architecture and dynamics of a supramolecular oxygen transport system in human homogentisate 1,2-Dioxygenase.

Journal of structural biology·2026

Same journal

Connecting pathways between mineralized fibrocartilage and bone at the Achilles tendon insertion.

Journal of structural biology·2026

Same journal

Structural and functional characterization of thermostable EstS1 esterase for BHET degradation.

Journal of structural biology·2026

Same journal

Following the white rabbit: multiscale 2D3D correlative imaging of bone structure.

Journal of structural biology·2026

Same journal

The mantis shrimp eye imaged in 3D using 4th generation synchrotron multiscale phase contrast tomography.

Journal of structural biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 2, 2026

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

ProPicker: Promptable segmentation for particle picking in cryogenic electron tomography.

Simon Wiedemann¹, Zalan Fabian², Mahdi Soltanolkotabi²

¹Technical University of Munich, Arcisstraße 21, 80333 Munich, Germany.

Journal of Structural Biology

|February 28, 2026

Summary

This summary is machine-generated.

ProPicker, a new AI tool, simplifies particle picking in 3D cryo-electron tomography (cryo-ET) images. This pretrained model efficiently detects cellular structures, improving data analysis speed and accuracy.

Keywords:

Cryo-ET Deep learning Object detection Particle picking Prompt Segmentation

More Related Videos

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Published on: March 19, 2021

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Related Experiment Videos

Last Updated: Mar 2, 2026

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Published on: March 19, 2021

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Cryo-electron tomography (cryo-ET) generates high-resolution 3D cellular images.
Particle picking, identifying specific structures in cryo-ET data, is crucial but challenging due to noise and complex cellular environments.

Purpose of the Study:

To introduce ProPicker, a novel pretrained, promptable 3D segmentation model for particle picking in cryo-ET.
To develop a flexible and data-efficient workflow for identifying diverse cellular particles.

Main Methods:

ProPicker utilizes a promptable 3D segmentation approach.
The model can be used directly with a prompt or fine-tuned for particle-specific accuracy.

Main Results:

ProPicker achieves performance comparable to state-of-the-art methods, up to 10x faster, using a single prompt.
The model demonstrates the ability to detect particles not encountered during training.
Fine-tuning ProPicker surpasses existing methods when limited training data is available.

Conclusions:

ProPicker offers a versatile and efficient solution for particle picking in cryo-ET data analysis.
The promptable nature of ProPicker enhances its applicability across various particle types and datasets.