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Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research
Published on: June 8, 2022
Tomographic spectroscopic imaging; an experimental proof of concept
W Van den Broek1, J Verbeeck, D Schryvers
1EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp, Belgium. wouter.vandenbroek@ua.ac.be
This study presents a more dose-efficient method for electron energy loss spectroscopy (EELS) data acquisition. The new technique uses projections and tomographic reconstruction, improving upon traditional energy-filtered imaging for EELS.
Area of Science:
- Materials Science
- Spectroscopy
- Electron Microscopy
Background:
- Traditional electron energy loss spectroscopy (EELS) data cube acquisition using energy-filtered images is dose inefficient due to electron beam blockage.
- Scanning probe methods offer perfect dose efficiency but are limited by slow acquisition speeds and small fields of view in nanoprobes.
Purpose of the Study:
- To demonstrate a novel, dose-efficient method for acquiring EELS data cubes.
- To present practical implementations, a geometrical model for projection angles, and experimental validation of the proposed technique.
Main Methods:
- Acquiring a set of projections of the EELS data cube.
- Utilizing tomographic reconstruction to reconstruct the full data cube from projections.
- Developing a geometrical model for precise quantification of projection angles.
Main Results:
- Successful experimental demonstration of the projection-based EELS data acquisition method.
- Validation of the geometrical model for accurate angle quantification.
- First successful experimental tomographic reconstruction of an EELS data cube using this technique on a standard instrument.
Conclusions:
- The proposed method offers a significant improvement in dose efficiency for EELS data cube acquisition compared to conventional energy-filtered series.
- This technique enables faster and more comprehensive EELS analysis without compromising data quality.
- The practical demonstration and successful reconstruction pave the way for wider adoption of this advanced EELS methodology.
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