Improved resolution in x-ray tomography by super-resolution

Dreier, Till; Peruzzi, Niccolò; Lundström, Ulf; Bech, Martin

doi:10.1364/ao.427934

Cited by 11 publications

(6 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…X-Ray Micro-Tomography: X-ray microtomography scans were acquired with a custom laboratory system [57] consisting of a prototype solid anode micro-focus X-ray source (Excillum AB, Sweden) and a photon counting Eiger 2R 500K detector (Dectris Ltd., Switzerland) with a pixel size of 75 μm, placed 0.55 m from the source as depicted in Figure 2A. The X-ray spot was focused to 10 μm at 70 kV acceleration voltage with an emission power of 15 W. Samples were placed 0.2 m from the source, covering their full width, resulting in an effective pixel size of 27.27 μm 2 , and a field-of-view of ≈28 × 14 mm 2 Processing and Reconstruction: For each scan, 1080 projections over 360°were acquired with an exposure time of 2 s per projection.…”

Section: Methodsmentioning

confidence: 99%

Elucidating the Bulk Morphology of Cellulose‐Based Conducting Aerogels with X‐Ray Microtomography

Oikonomou,

Dreier,

Sandéhn

et al. 2023

Adv Materials Technologies

Self Cite

View full text Add to dashboard Cite

Conducting cellulose composites are promising sustainable functional materials that have found application in energy devices, sensing and water purification. Herein, conducting aerogels are fabricated based on nanofibrillated cellulose and poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate, using the ice templating technique, and their bulk morphology is characterized with X‐ray microtomography. The freezing method (−20 °C in a freezer vs liquid nitrogen) does not impact the mean porosity of the aerogels but the liquid‐N2 aerogels have smaller pores. The integration of carbon fibers as addressing electrodes prior to freezing results in increased mean porosity and pore size in the liquid‐N2 aerogels signifying that the carbon fibers alter the morphology of the aerogels when the freezing is fast. Spatially resolved porosity and pore size distributions also reveal that the liquid‐N2 aerogels are more inhomogeneous. Independent of the freezing method, the aerogels have similar electrochemical properties. For aerogels without carbon fibers, freezer‐aerogels have higher compression modulus and are less stable under cycling compression fatigue test. This can be explained by higher porosity with larger pores in the center of liquid‐N2 aerogels and thinner pore walls. This work demonstrates that micro‐CT is a powerful tool for characterizing the morphology of aerogels in a non‐destructive and spatially resolved manner.

show abstract

Section: Methodsmentioning

confidence: 99%

Elucidating the Bulk Morphology of Cellulose‐Based Conducting Aerogels with X‐Ray Microtomography

Oikonomou,

Dreier,

Sandéhn

et al. 2023

Adv Materials Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…The technology is constantly evolving (Clark and Badea 2021 ), with efforts dedicated towards maximising key image quality indicators such as contrast-to-noise ratio (CNR) (Dudak et al 2016 ) and spatial resolution (Dreier et al 2021 ). At constant noise, CNR is determined by contrast, which in micro-CT is derived from differences in the attenuation of x-rays by the tissues they pass through.…”

Section: Introductionmentioning

confidence: 99%

Phase contrast micro-CT with adjustable in-slice spatial resolution at constant magnification

Zekavat,

Lioliou,

Roche i Morgó

et al. 2024

Phys. Med. Biol.

View full text Add to dashboard Cite

Objective: To report on a micro computed tomography (micro-CT) system capable of x-ray phase contrast imaging and of increasing spatial resolution at constant magnification. Approach: The micro-CT system implements the edge illumination (EI) method, which relies on two absorbing masks with periodically spaced transmitting apertures in the beam path; these split the beam into an array of beamlets and provide sensitivity to the beamlets' directionality, i.e., refraction. In EI, spatial resolution depends on the width of the beamlets rather than on the source/detector point spread function (PSF), meaning that resolution can be increased by decreasing the mask apertures, without changing the source/detector PSF or the magnification.Main results: We have designed a dedicated mask featuring multiple bands with differently sized apertures and used this to demonstrate that resolution is a tuneable parameter in our system, by showing that increasingly small apertures deliver increasingly detailed images. Phase contrast images of bar pattern-based resolution phantom and a biological sample (a mouse embryo) were obtained at multiple resolutions. Significance: The new micro-CT system could find application in areas where phase contrast is already known to provide superior image quality, while the added tuneable resolution functionality could enable more sophisticated analyses in these applications, e.g., by scanning samples at multiple scales.

show abstract

“…The potential to obtain high-definition images through image super-resolution reconstruction technology has attracted the attention of many researchers ( Lin et al., 2019 ; Yang et al., 2020 ; Dreier et al., 2021 ; Wei et al., 2022 ), but no reconstruction or application of laser confocal images has been reported in the literature. GAN and residual networks (ResNet) are two representative deep-learning networks.…”

Section: Introductionmentioning

confidence: 99%

“…The potential to obtain high-definition images through image super-resolution reconstruction technology has attracted the attention of many researchers (Lin et al, 2019;Yang et al, 2020;Dreier et al, 2021;Wei et al, 2022) SRGAN has the same overall structure as GAN. It is composed of a generative network and a discriminant network, and the perceived loss is used as the loss function (Ledig et al, 2017;Li and Zhang, 2022;Singla et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Super-resolution reconstruction, recognition, and evaluation of laser confocal images of hyperaccumulator Solanum nigrum endocytosis vesicles based on deep learning: Comparative study of SRGAN and SRResNet

Liu

et al. 2023

Front. Plant Sci.

View full text Add to dashboard Cite

It is difficult for laser scanning confocal microscopy to obtain high- or ultra-high-resolution laser confocal images directly, which affects the deep mining and use of the embedded information in laser confocal images and forms a technical bottleneck in the in-depth exploration of the microscopic physiological and biochemical processes of plants. The super-resolution reconstruction model (SRGAN), which is based on a generative adversarial network and super-resolution reconstruction model (SRResNet), which is based on a residual network, was used to obtain single and secondary super-resolution reconstruction images of laser confocal images of the root cells of the hyperaccumulator Solanum nigrum. Using the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and mean opinion score (MOS), the models were evaluated by the image effects after reconstruction and were applied to the recognition of endocytic vesicles in Solanum nigrum root cells. The results showed that the single reconstruction and the secondary reconstruction of SRGAN and SRResNet improved the resolution of laser confocal images. PSNR, SSIM, and MOS were clearly improved, with a maximum PSNR of 47.690. The maximum increment of PSNR and SSIM of the secondary reconstruction images reached 21.7% and 2.8%, respectively, and the objective evaluation of the image quality was good. However, overall MOS was less than that of the single reconstruction, the perceptual quality was weakened, and the time cost was more than 130 times greater. The reconstruction effect of SRResNet was better than that of SRGAN. When SRGAN and SRResNet were used for the recognition of endocytic vesicles in Solanum nigrum root cells, the clarity of the reconstructed images was obviously improved, the boundary of the endocytic vesicles was clearer, and the number of identified endocytic vesicles increased from 6 to 9 and 10, respectively, and the mean fluorescence intensity was enhanced by 14.4% and 7.8%, respectively. Relevant research and achievements are of great significance for promoting the application of deep learning methods and image super-resolution reconstruction technology in laser confocal image studies.

show abstract

Improved resolution in x-ray tomography by super-resolution

Cited by 11 publications

References 44 publications

Elucidating the Bulk Morphology of Cellulose‐Based Conducting Aerogels with X‐Ray Microtomography

Elucidating the Bulk Morphology of Cellulose‐Based Conducting Aerogels with X‐Ray Microtomography

Phase contrast micro-CT with adjustable in-slice spatial resolution at constant magnification

Super-resolution reconstruction, recognition, and evaluation of laser confocal images of hyperaccumulator Solanum nigrum endocytosis vesicles based on deep learning: Comparative study of SRGAN and SRResNet

Contact Info

Product

Resources

About