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Proceedings Paper

Morphological filtering based on the Minkowski functionals in 3D for segmentation of macromolecular structures in intact eukaryotic cells depicted by cryo-electron tomography
Author(s): Holger F. Boehm; Ferdinand Jamitzki; Roberto A. Monetti; Dirk Mueller; Alexandros Linaroudis; Reiner Hegerl; Ernst J. Rummeny; Christoph W. Raeth
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Paper Abstract

In this contribution, we propose a novel approach to the segmentation of tomographic image data considering topological properties of binarized image components expressed in terms of the Minkowski Functionals in 3D. Electron tomography is a non-invasive method for three-dimensional (3D) reconstruction of cellular sub-structures from a series of projection images (i.e. from a tilt series) recorded with a transmission electron microscope. Data obtained by electron tomography provide a rich source of quantitative information concerning the structural composition and organization of cellular components. It allows to obtain 3D information on structural cellular arrangements at a significantly higher resolution than any other of the currently available imaging modalities. A major challenge, in this context, is the segmentation of the image data with respect to the identification macro-molecular structures such as the actin-cytoskeleton or cell organelles. We introduce a morphological filtering algorithm based on the Minkowski Functionals in 3D for segmentation of macromolecular structures in intact eukaryotic cells depicted by cryo-electron tomography. In mathematical topology, multi-dimensional convex objects can be characterized with respect to shape, structure, and the connectivity of their components using a set of morphological descriptors known as the Minkowski functionals. In a 3D-Euclidian space, these correspond to volume, surface area, mean integral curvature, and the Euler-Poincare characteristic. The morphological filtering procedure is applied to a 3D image data of an intact, ice-embedded Dictyostelium cell obtained by low dose transmission electron microscopy using a tilt series of -50° to +41.5° with an increment of 1.5°. Our method allows to separate cellular components with predefined textural properties, e.g. filamentary or globular structures, from the image data, which may then be studied and interpreted further.

Paper Details

Date Published: 29 April 2005
PDF: 8 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.593717
Show Author Affiliations
Holger F. Boehm, Technische Univ. Muenchen (Germany)
Max-Planck-Institut fuer extraterrestrische Physik (Germany)
Ferdinand Jamitzki, Max-Planck-Institut fuer extraterrestrische Physik (Germany)
Roberto A. Monetti, Max-Planck-Institut fuer extraterrestrische Physik (Germany)
Dirk Mueller, Technische Univ. Muenchen (Germany)
Max-Planck-Institut fuer extraterrestrische Physik (Germany)
Alexandros Linaroudis, Max-Planck-Institut fuer Biochemie (Germany)
Reiner Hegerl, Max-Planck-Institut fuer Biochemie (Germany)
Ernst J. Rummeny, Technische Univ. Muenchen (Germany)
Christoph W. Raeth, Max-Planck-Institut fuer extraterrestrische Physik (Germany)

Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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