Two-Stage Alignment of FIB-SEM Images of Rock Samples
| Autor: | Anton Kornilov, Ivan Yakimchuk, Ilia V. Safonov, Iryna Reimers |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
stack of images
Computer science 02 engineering and technology lcsh:Computer applications to medicine. Medical informatics Focused ion beam Signal lcsh:QA75.5-76.95 Article 03 medical and health sciences porous media Stack (abstract data type) Radiology Nuclear Medicine and imaging lcsh:Photography Electrical and Electronic Engineering Anisotropy digital rock 030304 developmental biology 0303 health sciences alignment FIB-SEM 021001 nanoscience & nanotechnology lcsh:TR1-1050 Computer Graphics and Computer-Aided Design Sample (graphics) lcsh:R858-859.7 Computer Vision and Pattern Recognition Affine transformation Tomography lcsh:Electronic computers. Computer science 0210 nano-technology Fiducial marker Algorithm |
| Zdroj: | Journal of Imaging Journal of Imaging, Vol 6, Iss 107, p 107 (2020) Volume 6 Issue 10 |
| ISSN: | 2313-433X |
| Popis: | Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are based on a comparison of two adjacent slices. However, such algorithms are easily confused by anisotropy in the sample structure or even experiment geometry in the case of porous media. This may lead to significant distortions in the pore space geometry, if there are no stable fiducial marks in the frame. In this paper, we propose a new method, which meaningfully extends existing alignment procedures. Our technique allows the correction of random misalignments between slices and, at the same time, preserves the overall geometrical structure of the specimen. We consider displacements produced by existing alignment algorithms as a signal and decompose it into low and high-frequency components. Final transformations exclude slow variations and contain only high frequency variations that represent random shifts that need to be corrected. The proposed algorithm can operate with not only translations but also with arbitrary affine transformations. We demonstrate the performance of our approach on a synthetic dataset and two real FIB-SEM images of natural rock. |
| Databáze: | OpenAIRE |
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