2,179 research outputs found
Shot noise-mitigated secondary electron imaging with ion count-aided microscopy
Modern science is dependent on imaging on the nanoscale, often achieved
through processes that detect secondary electrons created by a highly focused
incident charged particle beam. Scanning electron microscopy is employed in
applications such as critical-dimension metrology and inspection for
semiconductor devices, materials characterization in geology, and examination
of biological samples. With its applicability to non-conducting materials (not
requiring sample coating before imaging), helium ion microscopy (HIM) is
especially useful in the high-resolution imaging of biological samples such as
animal organs, tumor cells, and viruses. However, multiple types of measurement
noise limit the ultimate trade-off between image quality and the incident
particle dose, which can preclude useful imaging of dose-sensitive samples.
Existing methods to improve image quality do not fundamentally mitigate the
noise sources. Furthermore, barriers to assigning a physically meaningful scale
make these modalities qualitative. Here we introduce ion count-aided microscopy
(ICAM), which is a quantitative imaging technique that uses statistically
principled estimation of the secondary electron yield. With a readily
implemented change in data collection, ICAM nearly eliminates the influence of
source shot noise -- the random variation in the number of incident ions in a
fixed time duration. In HIM, we demonstrate 3x dose reduction; based on a good
match between these empirical results and theoretical performance predictions,
the dose reduction factor is larger when the secondary electron yield is
higher. ICAM thus facilitates imaging of fragile samples and may make imaging
with heavier particles more attractive
Continuous-Time Modeling and Analysis of Particle Beam Metrology
Particle beam microscopy (PBM) performs nanoscale imaging by pixelwise
capture of scalar values representing noisy measurements of the response from
secondary electrons (SEs) integrated over a dwell time. Extended to metrology,
goals include estimating SE yield at each pixel and detecting differences in SE
yield across pixels; obstacles include shot noise in the particle source as
well as lack of knowledge of and variability in the instrument response to
single SEs. A recently introduced time-resolved measurement paradigm promises
mitigation of source shot noise, but its analysis and development have been
largely limited to estimation problems under an idealization in which SE bursts
are directly and perfectly counted. Here, analyses are extended to error
exponents in feature detection problems and to degraded measurements that are
representative of actual instrument behavior for estimation problems. For
estimation from idealized SE counts, insights on existing estimators and a
superior estimator are also provided. For estimation in a realistic PBM imaging
scenario, extensions to the idealized model are introduced, methods for model
parameter extraction are discussed, and large improvements from time-resolved
data are presented.Comment: 14 pages, 10 figure
Scanning electron microscope image signal-to-noise ratio monitoring for micro-nanomanipulation.
International audienceAs an imaging system, scanning electron microscope (SEM) performs an important role in autonomous micro-nanomanipulation applications. When it comes to the sub micrometer range and at high scanning speeds, the images produced by the SEM are noisy and need to be evaluated or corrected beforehand. In this article, the quality of images produced by a tungsten gun SEM has been evaluated by quantifying the level of image signal-to-noise ratio (SNR). In order to determine the SNR, an efficient and online monitoring method is developed based on the nonlinear filtering using a single image. Using this method, the quality of images produced by a tungsten gun SEM is monitored at different experimental conditions. The derived results demonstrate the developed method's efficiency in SNR quantification and illustrate the imaging quality evolution in SEM
Twin-beam sub-shot-noise raster-scanning microscope
By exploiting the quantised nature of light, we demonstrate a sub-shot-noise scanning optical transmittance microscope. Our microscope demonstrates, with micron scale resolution, a factor of improvement in precision of 1.76(9) in transmittance estimation gained per probe photon relative to the theoretical model, a shot-noise-limited source of light, in an equivalent single-pass classical version of the same experiment using the same number of photons detected with a 90% efficient detector. This would allow us to observe photosensitive samples with nearly twice the precision, without sacrificing image resolution or increasing optical power to improve signal-to-noise ratio. Our setup uses correlated twin-beams produced by parametric down-conversion, and a hybrid detection scheme comprising photon-counting-based feed-forward and a highly efficient CCD camera
A CANDLE for a deeper in-vivo insight
A new Collaborative Approach for eNhanced Denoising under Low-light Excitation (CANDLE) is introduced for the processing of 3D laser scanning multiphoton microscopy images. CANDLE is designed to be robust for low signal-to-noise ratio (SNR) conditions typically encountered when imaging deep in scattering biological specimens. Based on an optimized non-local means filter involving the comparison of filtered patches, CANDLE locally adapts the amount of smoothing in order to deal with the noise inhomogeneity inherent to laser scanning fluorescence microscopy images. An extensive validation on synthetic data, images acquired on microspheres and in vivo images is presented. These experiments show that the CANDLE filter obtained competitive results compared to a state-of-the-art method and a locally adaptive optimized non-local means filter, especially under low SNR conditions (PSNR < 8 dB). Finally, the deeper imaging capabilities enabled by the proposed filter are demonstrated on deep tissue in vivo images of neurons and fine axonal processes in the Xenopus tadpole brain.We want to thank Florian Luisier for providing free plugin of his PureDenoise filter. We also want to thank Markku Makitalo for providing the code of their OVST. This study was supported by the Canadian Institutes of Health Research (CIHR, MOP-84360 to DLC and MOP-77567 to ESR) and Cda (CECR)-Gevas-OE016. MM holds a fellowship from the Deutscher Akademischer Austasch Dienst (DAAD) and a McGill Principal's Award. ESR is a tier 2 Canada Research Chair. This work has been partially supported by the Spanish Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001. This work benefited from the use of ImageJ.Coupé, P.; Munz, M.; Manjón Herrera, JV.; Ruthazer, ES.; Collins, DL. (2012). A CANDLE for a deeper in-vivo insight. Medical Image Analysis. 16(4):849-864. https://doi.org/10.1016/j.media.2012.01.002S84986416
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