Enhanced FIB-SEM systems for large-volume 3D imaging
Abstract
Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 106 µm3. These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, Drosophila brain, and Chlamydomonas reinhardtii to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- C Shan Xu
- Kenneth J Hayworth
- Zhiyuan Lu
- Krishna K Niyogi
- Eva Nogales
- Harald F Hess
U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division (SISGRKN)
- Krishna K Niyogi
- Eva Nogales
Gordon and Betty Moore Foundation (GBMF3070)
- Krishna K Niyogi
NIH (R01 NS-039444)
- Richard J Weinberg
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All of the vertebrate animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#13-258.0) of UNC. UNC's PHS Assurance number is D16-00256 (A3410-01); the AALAC Unit number is 000329.
Copyright
© 2017, Xu et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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