Automatic Alignment of Transmission Electron Microscope Tilt Series without Fiducial Markers

“…Feature tracking uses regions of high contrast or intensity as fiducial markers [13,14]. It requires the identification of suitable regions of high contrast that remain visible throughout the tilt series.…”

Section: Introductionmentioning

confidence: 99%

Physically motivated global alignment method for electron tomography

Sanders

Prange

Akatay

et al. 2015

Adv Struct Chem Imag

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Electron tomography is widely used for nanoscale determination of 3-D structures in many areas of science. Determining the 3-D structure of a sample from electron tomography involves three major steps: acquisition of sequence of 2-D projection images of the sample with the electron microscope, alignment of the images to a common coordinate system, and 3-D reconstruction and segmentation of the sample from the aligned image data. The resolution of the 3-D reconstruction is directly influenced by the accuracy of the alignment, and therefore, it is crucial to have a robust and dependable alignment method. In this paper, we develop a new alignment method which avoids the use of markers and instead traces the computed paths of many identifiable 'local' center-of-mass points as the sample is rotated. Compared with traditional correlation schemes, the alignment method presented here is resistant to cumulative error observed from correlation techniques, has very rigorous mathematical justification, and is very robust since many points and paths are used, all of which inevitably improves the quality of the reconstruction and confidence in the scientific results.

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“…The method requires a long preparation time and the use of markers can result in artifacts in the reconstructed image. Instead of fiducial markers, features in the projection data can also act as markers, [7].…”

Section: Introductionmentioning

confidence: 99%

Automatic Optimization of Alignment Parameters for Tomography Datasets

Bleichrodt

Batenburg

2013

Image Analysis

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Abstract. As tomographic imaging is being performed at increasingly smaller scales, the stability of the scanning hardware is of great importance to the quality of the reconstructed image. Instabilities lead to perturbations in the geometrical parameters used in the acquisition of the projections. In particular for electron tomography and high-resolution X-ray tomography, small instabilities in the imaging setup can lead to severe artifacts. We present a novel alignment algorithm for recovering the true geometrical parameters after the object has been scanned, based on measured data. Our algorithm employs an optimization algorithm that combines alignment with reconstruction. We demonstrate that problemspecific design choices made in the implementation are vital to the success of the method. The algorithm is tested in a set of simulation experiments. Our experimental results indicate that the method is capable of aligning tomography datasets with considerably higher accuracy compared to standard cross-correlation methods.

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Automatic Alignment of Transmission Electron Microscope Tilt Series without Fiducial Markers

Cited by 88 publications

References 23 publications

Conditional solutions for the affine reconstruction of N-views

Conditional solutions for the affine reconstruction of N-views

Physically motivated global alignment method for electron tomography

Automatic Optimization of Alignment Parameters for Tomography Datasets

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