Chapter 12
Segmentation of Features in Electron
Tomographic Reconstructions
Niels Volkmann
Abstract Electron tomography is the most widely applicable method for obtaining
three-dimensional information from biological samples by electron microscopy.
However, owing to the complexity and low signal-to-noise ratio of the reconstructions, direct interpretation of their three-dimensional content is not straight
forward. This chapter describes computational approaches designed to extract the
most accurate information possible from biological electron tomograms.
12.1 Introduction
Modern biology has now advanced to a stage where structural information about
isolated macromolecules and assemblies must be integrated to define higher-order
cellular functions. Electron tomography is the most widely applicable method for
obtaining three-dimensional information by electron microscopy and has become a
powerful tool for revealing the molecular architecture of biological cells and tissues
[1–3]. The achievable resolution (3–6 nm) is intermediate between that achievable
by light microscopy and X-ray crystallography or high-resolution single-particle
electron cryo-microscopy, thus capable of bridging the gap between live-cell
imaging and atomic resolution structures. In the field of biology it has been realized
that electron tomography, in particular its cryo variant, is capable of providing a
complete, molecular resolution three-dimensional mapping of entire proteoms, at
least in principle [4, 5]. However, to realize this goal, the relevant information needs
to be extracted from the tomograms by means of segmentation. This task is complicated by several factors:
N. Volkmann (&)
Sanford Burnham Prebys Medical Discovery Institute,
10901 N Torrey Pines Road, La Jolla, CA 92037, USA
e-mail: niels@burnham.org
© Springer International Publishing AG 2018
E. Hanssen (ed.), Cellular Imaging, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-3-319-68997-5_12
301
Segmentation of Features in Electron
Tomographic Reconstructions
Niels Volkmann
Abstract Electron tomography is the most widely applicable method for obtaining
three-dimensional information from biological samples by electron microscopy.
However, owing to the complexity and low signal-to-noise ratio of the reconstructions, direct interpretation of their three-dimensional content is not straight
forward. This chapter describes computational approaches designed to extract the
most accurate information possible from biological electron tomograms.
12.1 Introduction
Modern biology has now advanced to a stage where structural information about
isolated macromolecules and assemblies must be integrated to define higher-order
cellular functions. Electron tomography is the most widely applicable method for
obtaining three-dimensional information by electron microscopy and has become a
powerful tool for revealing the molecular architecture of biological cells and tissues
[1–3]. The achievable resolution (3–6 nm) is intermediate between that achievable
by light microscopy and X-ray crystallography or high-resolution single-particle
electron cryo-microscopy, thus capable of bridging the gap between live-cell
imaging and atomic resolution structures. In the field of biology it has been realized
that electron tomography, in particular its cryo variant, is capable of providing a
complete, molecular resolution three-dimensional mapping of entire proteoms, at
least in principle [4, 5]. However, to realize this goal, the relevant information needs
to be extracted from the tomograms by means of segmentation. This task is complicated by several factors:
N. Volkmann (&)
Sanford Burnham Prebys Medical Discovery Institute,
10901 N Torrey Pines Road, La Jolla, CA 92037, USA
e-mail: niels@burnham.org
© Springer International Publishing AG 2018
E. Hanssen (ed.), Cellular Imaging, Biological and Medical Physics,
Biomedical Engineering, https://doi.org/10.1007/978-3-319-68997-5_12
301