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Related Experiment Video

Updated: Oct 17, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

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Published on: August 13, 2014

Whole-cell organelle segmentation in volume electron microscopy.

Larissa Heinrich¹, Davis Bennett¹, David Ackerman¹

¹Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.

|October 7, 2021

Summary

This study presents an automated method for 3D cell reconstruction, enabling detailed analysis of organelle interactions. The OpenOrganelle platform provides open-access data and tools for advancing cell biology research.

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Last Updated: Oct 17, 2025

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Published on: August 13, 2014

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Published on: June 9, 2022

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

Area of Science:

Cell Biology
Biophysics
Computational Biology

Background:

Understanding cellular organization requires high-resolution 3D reconstruction of organelles.
Scalable automated methods are crucial for achieving whole-cell reconstructions.

Purpose of the Study:

To develop and validate automated deep learning methods for segmenting and reconstructing cellular organelles from FIB-SEM data.
To create an open-access resource for 3D cell biology research.

Main Methods:

Annotation of 35 organelle classes in FIB-SEM datasets (4nm and 8nm resolution).
Training deep learning models for segmentation of cellular structures.
Validation of segmentation performance and application in quantitative analysis.

Main Results:

Successful segmentation and 3D reconstruction of diverse organelles from multiple cell types.
Demonstration of automated quantification of organelle spatial interactions.
Development of automatic registration for correlative light and electron microscopy.

Conclusions:

Automated 3D reconstruction methods significantly advance the study of cellular architecture.
The OpenOrganelle repository facilitates global access to data, code, and models for improved cell reconstruction.
This work enables new quantitative analyses of cellular organization and correlative imaging.