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Müller, A. ; Schmidt, D.* ; Albrecht, J.P.* ; Rieckert, L.* ; Otto, M.* ; Galicia Garcia, L.E. ; Fabig, G.* ; Solimena, M. ; Weigert, M.*

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets.

Nat. Protoc., DOI: 10.1038/s41596-024-00957-5 (2024)
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Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and spatial analysis is necessary. Here we describe a practical and annotation-efficient pipeline for organelle-specific segmentation, spatial analysis and visualization of large volume electron microscopy datasets using freely available, user-friendly software tools that can be run on a single standard workstation. The procedures are aimed at researchers in the life sciences with modest computational expertise, who use volume electron microscopy and need to generate three-dimensional (3D) segmentation labels for different types of cell organelles while minimizing manual annotation efforts, to analyze the spatial interactions between organelle instances and to visualize the 3D segmentation results. We provide detailed guidelines for choosing well-suited segmentation tools for specific cell organelles, and to bridge compatibility issues between freely available open-source tools, we distribute the critical steps as easily installable Album solutions for deep learning segmentation, spatial analysis and 3D rendering. Our detailed description can serve as a reference for similar projects requiring particular strategies for single- or multiple-organelle analysis, which can be achieved with computational resources commonly available to single-user setups.
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Publication type Article: Journal article
Document type Review
Keywords Reconstruction; Microtubules; Region
Language english
Publication Year 2024
HGF-reported in Year 2024
ISSN (print) / ISBN 1754-2189
e-ISSN 1750-2799
Journal Nature Protocols
Publisher Nature Publishing Group
Publishing Place Heidelberger Platz 3, Berlin, 14197, Germany
Reviewing status Peer reviewed
Institute(s) Institute of Pancreatic Islet Research (IPI)
POF-Topic(s) 90000 - German Center for Diabetes Research
Research field(s) Helmholtz Diabetes Center
PSP Element(s) G-502600-001
Grants Helmholtz Imaging
German Ministry for Education and Research (BMBF)
Innovative Medicines Initiative 2 Joint Undertaking
European Union's Horizon 2020 research and innovation program
European Federation of Pharmaceutical Industries and Associations (EFPIA)
Swiss State Secretariat for Education, Research and Innovation
Carl Gustav Carus Faculty of Medicine at TU Dresden
ELISIR program of the Ecole Polytechnique Federale de Lausanne School of Life Sciences
CARIGEST SA
Electron Microscopy and Histology Facility
DOI 10.1038/s41596-024-00957-5
WOS ID 001175701700001
Scopus ID 85186606371
PubMed ID 38424188
Erfassungsdatum 2024-04-29
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