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Smart Align—a new tool for robust non-rigid registration of scanning microscope data
Smart Align—a new tool for robust non-rigid registration of scanning microscope data
- Source :
- Advanced Structural and Chemical Imaging
- Publisher :
- Springer Nature
-
Abstract
- Many microscopic investigations of materials may benefit from the recording of multiple successive images. This can include techniques common to several types of microscopy such as frame averaging to improve signal-to-noise ratios (SNR) or time series to study dynamic processes or more specific applications. In the scanning transmission electron microscope, this might include focal series for optical sectioning or aberration measurement, beam damage studies or camera-length series to study the effects of strain; whilst in the scanning tunnelling microscope, this might include bias-voltage series to probe local electronic structure. Whatever the application, such investigations must begin with the careful alignment of these data stacks, an operation that is not always trivial. In addition, the presence of low-frequency scanning distortions can introduce intra-image shifts to the data. Here, we describe an improved automated method of performing non-rigid registration customised for the challenges unique to scanned microscope data specifically addressing the issues of low-SNR data, images containing a large proportion of crystalline material and/or local features of interest such as dislocations or edges. Careful attention has been paid to artefact testing of the non-rigid registration method used, and the importance of this registration for the quantitative interpretation of feature intensities and positions is evaluated.
- Subjects :
- Microscope
Materials science
Optical sectioning
Scanning electron microscope
Image registration
02 engineering and technology
01 natural sciences
law.invention
law
0103 physical sciences
Microscopy
Scanning transmission electron microscopy
Chemical Engineering (miscellaneous)
Radiology, Nuclear Medicine and imaging
Computer vision
Spectroscopy
010302 applied physics
business.industry
Physics
Frame (networking)
021001 nanoscience & nanotechnology
Chemistry
Feature (computer vision)
Artificial intelligence
0210 nano-technology
business
Subjects
Details
- Language :
- English
- ISSN :
- 21980926
- Volume :
- 1
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Advanced Structural and Chemical Imaging
- Accession number :
- edsair.doi.dedup.....82a7fda867ad8dac0a2166df4d5598ab
- Full Text :
- https://doi.org/10.1186/s40679-015-0008-4