relays on the sectioning system. In addition, the sectioning process lead to a rupture
of the matter continuity in the sample and to deformations induced by sectioning
forces when ultramicrotomes are used. Deformations and anisotropy should be
taken in consideration to align images. Thus, a pre-alignment based on rigid
alignment approaches is needed and, when deformations occur, it should be followed by elastic transformations computation to correct the deformations induced
by sectioning. In both cases the methods used for axial-tomography described in
previous sections of this chapter are valuable for both, rigid and elastic alignment.
However, specific methods, based on squared difference [45, 46] or landmarks
defined either manually or automatically using specific definition [47] or using
SIFT [48], have been proposed for serial image alignment.
7.5 Conclusion
Alignment of images in tomography is a crucial step to succeed in accurate
reconstructions process. In spite that several methods and algorithms exist, while
tomography trends towards new frontiers such as 3D chemical mapping, there is an
active research on this field of image processing. Thus, from classical approaches,
based on cross-correlation and on the use of gold-beads as fiducial markers, we
move nowadays to more robust methods allowing the correction of image deformations or the automatic determination of inherent landmarks. Thus, it is expected
that in near future, the advances in image alignment will contribute to the development of high-through flow tomography integrated in a multimodal and multiscale
3D imaging approach.
References
1. B. Turoňová, L. Marsalek, P. Slusallek, On geometric artifacts in cryo electron tomography.
Ultramicroscopy 163, 48–61 (2016)
2. J. Frank, B.F. McEwen, M. Radermacher, J.N. Turner, C.L. Rieder, Three-dimensional
tomographic reconstruction in high voltage electron microscopy. J. Electron Microsc. Tech. 6,
193–205 (1987)
3. J. Frank, B.F. McEwen, Alignment by cross-correlation. Electron Tomogr (Springer Science,
1992), pp. 205–213
4. R. Guckenberger, Determination of a common origin in the micrographs of titl series in
three-dimensional electron microscopy. Ultramicroscopy 9, 167–174 (1982)
5. S. Brandt, J. Heikkonen, P. Engehardt, Automatic alignment of transmission electron
microscope tilt series without fiducial markers. J. Struct. Biol. 136, 201–213 (2001)
6. M. Cao, H.-B. Zhang, Y. Lu, R. Nishi, A. Takaoka, Formation and reduction of streak
artefacts in electron tomography. J. Microsc. 239(1), 66–71 (2010)
7. Y. Cong, J.A. Kovacs, W. Wriggers, 2D fast rotational matching for image processing of
biophysical data. J. Struct. Biol. 144(1–2), 51–60 (2003)
7 Alignment of Tilt Series
205
of the matter continuity in the sample and to deformations induced by sectioning
forces when ultramicrotomes are used. Deformations and anisotropy should be
taken in consideration to align images. Thus, a pre-alignment based on rigid
alignment approaches is needed and, when deformations occur, it should be followed by elastic transformations computation to correct the deformations induced
by sectioning. In both cases the methods used for axial-tomography described in
previous sections of this chapter are valuable for both, rigid and elastic alignment.
However, specific methods, based on squared difference [45, 46] or landmarks
defined either manually or automatically using specific definition [47] or using
SIFT [48], have been proposed for serial image alignment.
7.5 Conclusion
Alignment of images in tomography is a crucial step to succeed in accurate
reconstructions process. In spite that several methods and algorithms exist, while
tomography trends towards new frontiers such as 3D chemical mapping, there is an
active research on this field of image processing. Thus, from classical approaches,
based on cross-correlation and on the use of gold-beads as fiducial markers, we
move nowadays to more robust methods allowing the correction of image deformations or the automatic determination of inherent landmarks. Thus, it is expected
that in near future, the advances in image alignment will contribute to the development of high-through flow tomography integrated in a multimodal and multiscale
3D imaging approach.
References
1. B. Turoňová, L. Marsalek, P. Slusallek, On geometric artifacts in cryo electron tomography.
Ultramicroscopy 163, 48–61 (2016)
2. J. Frank, B.F. McEwen, M. Radermacher, J.N. Turner, C.L. Rieder, Three-dimensional
tomographic reconstruction in high voltage electron microscopy. J. Electron Microsc. Tech. 6,
193–205 (1987)
3. J. Frank, B.F. McEwen, Alignment by cross-correlation. Electron Tomogr (Springer Science,
1992), pp. 205–213
4. R. Guckenberger, Determination of a common origin in the micrographs of titl series in
three-dimensional electron microscopy. Ultramicroscopy 9, 167–174 (1982)
5. S. Brandt, J. Heikkonen, P. Engehardt, Automatic alignment of transmission electron
microscope tilt series without fiducial markers. J. Struct. Biol. 136, 201–213 (2001)
6. M. Cao, H.-B. Zhang, Y. Lu, R. Nishi, A. Takaoka, Formation and reduction of streak
artefacts in electron tomography. J. Microsc. 239(1), 66–71 (2010)
7. Y. Cong, J.A. Kovacs, W. Wriggers, 2D fast rotational matching for image processing of
biophysical data. J. Struct. Biol. 144(1–2), 51–60 (2003)
7 Alignment of Tilt Series
205