New Mathematical Method Sharpens X-Ray 3D Imaging to 20 Nanometers: Lund Team Reports About Threefold Gain in Optica
An international team has developed a method that produces significantly higher quality three-dimensional X-ray images for X-ray nanotomography. The paper by Viktor Nikitin and colleagues appears in Optica, with Marcus Carlsson, a mathematics researcher at Lund University, as last author leading the mathematical and algorithmic work.
Carlsson said the work shows the limitation has not only been in the X-ray optics, but also in the mathematics used to reconstruct the image.
The new method can distinguish structures down to 20 nanometers. By comparison, a human hair is between 80,000 and 100,000 nanometers thick. In the current study, image resolution improved by around threefold, making fine structures such as synapses and mitochondria visible in three dimensions.
Researchers normally use electron microscopy at the nanoscale, but samples must be cut into very thin slices for three-dimensional imaging and the process permanently damages the material, the team noted. X-ray imaging can examine much larger samples in three dimensions without cutting them apart, with the challenge lying in extracting information from enormous data volumes.
Carlsson said better mathematical models and optimization algorithms can extract significantly more information from the same measurement data, opening possibilities in biological imaging and other fields needing nondestructive three-dimensional study. The paper, using the bilinear Hessian method, carries digital object identifier 10.1364/optica.603920.
Published by GSM · USA (original Chinese edition)
Photo: 图：位于瑞典隆德的 MAX IV 同步辐射实验室建筑。Johan Wessman 摄，CC BY 2.0，经 Wikimedia Commons / Photo: 20200517 Max IV i Lund 002 (49913522522). By Johan Wessman, CC BY 2.0, via Wikimedia Commons
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