• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.533-538
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• 2015

Thermal characterization of individual pixels in microbolometer infrared image sensors is needed for optimal design and improved performance. In this work, we used thermoreflectance microscopy on uncooled microbolometer image sensors to investigate the thermal characteristics of individual pixels. Two types of microbolometer image sensors with a shared-anchor structure were fabricated and thermally characterized at various biases and vacuum levels by measuring the temperature distribution on the surface of the microbolometers. The results show that thermoreflectance microscopy can be a useful thermal characterization tool for microbolometer image sensors.

• Applied Microscopy
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• v.46 no.1
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• pp.6-13
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• 2016

Fluorescence lifetime imaging microscopy (FLIM) has been considered an effective technique to investigate chemical properties of the specimens, especially of biological samples. Despite of this advantageous trait, researchers in this field have had difficulties applying FLIM to their systems because acquiring an image using FLIM consumes too much time. Although analog mean-delay (AMD) method was introduced to enhance the imaging speed of commonly used FLIM based on time-correlated single photon counting (TCSPC), a real-time image reconstruction using AMD method has not been implemented due to its data processing obstacles. In this paper, we introduce a real-time image restoration of AMD-FLIM through fast parallel data processing by using Threading Building Blocks (TBB; Intel) and octa-core processor (i7-5960x; Intel). Frame rate of 3.8 frames per second was achieved in $1,024{\times}1,024$ resolution with over 4 million lifetime determinations per second and measurement error within 10%. This image acquisition speed is 184 times faster than that of single-channel TCSPC and 9.2 times faster than that of 8-channel TCSPC (state-of-art photon counting rate of 80 million counts per second) with the same lifetime accuracy of 10% and the same pixel resolution.

• Journal of Microbiology and Biotechnology
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• v.33 no.3
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• pp.348-355
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• 2023

Epifluorescence microscopy with image analysis was evaluated as a biofilm quantification method (i.e., quantification of surface area colonized by biofilms), in comparison with crystal violet (CV) staining. We performed different experiments to generate multispecies biofilms with natural and artificial bacterial assemblages. First, four species were inoculated daily in 16 different sequences to form biofilms (surface colonization, 0.1%-56.6%). Second, a 9-species assemblage was allowed to form biofilms under 10 acylase treatment episodes (33.8%-55.6%). The two methods comparably measured the quantitative variation in biofilms, exhibiting a strong positive relationship (R² ≥ 0.7). Moreover, the two methods exhibited similar levels of variation coefficients. Finally, six synthetic and two natural consortia were allowed to form biofilms for 14 days, and their temporal dynamics were monitored. The two methods were comparable in quantifying four biofilms colonizing ≥18.7% (R² ≥ 0.64), but not for the other biofilms colonizing ≤ 3.7% (R² ≤ 0.25). In addition, the two methods exhibited comparable coefficients of variation in the four biofilms. Microscopy and CV staining comparably measured the quantitative variation of biofilms, exhibiting a strongly positive relationship, although microscopy cannot appropriately quantify the biofilms below the threshold colonization. Microscopy with image analysis is a promising approach for easily and rapidly estimating absolute quantity of multispecies biofilms.

• Current Optics and Photonics
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• v.5 no.5
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• pp.524-531
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• 2021

In an integral-imaging microscopy (IIM) system, a microlens array (MLA) is the primary optical element; however, surface errors impede the resolution of a raw image's details. Calibration is a major concern with regard to incorrect projection of the light rays. A ray-tracing-based calibration method for an IIM camera is proposed, to address four errors: MLA decentering, rotational, translational, and subimage-scaling errors. All of these parameters are evaluated using the reference image obtained from the ray-traced white image. The areas and center points of the microlens are estimated using an "8-connected" and a "center-of-gravity" method respectively. The proposed approach significantly improves the rectified-image quality and nonlinear image brightness for an IIM system. Numerical and optical experiments on multiple real objects demonstrate the robustness and effectiveness of our proposed method, which achieves on average a 35% improvement in brightness for an IIM raw image.

• Applied Microscopy
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• v.44 no.2
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• pp.74-78
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• 2014

Dislocation density and distribution in epitaxial GaAs layer on Si are evaluated quantitatively and effectively using image processing of transmission electron microscopy image. In order to evaluate dislocation density and distribution, three methods are introduced based on line-intercept, line-length measurement and our coding with line-scanning method. Our coding method based on line-scanning is used to detect the dislocations line-by-line effectively by sweeping a thin line with the width of one pixel. The proposed method has advances in the evaluation of dislocation density and distribution. Dislocations can be detected automatically and continuously by a sweeping line in the code. Variation of dislocation density in epitaxial GaAs films can be precisely analyzed along the growth direction on the film.

• Applied Microscopy
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• v.45 no.2
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• pp.101-105
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• 2015

Numerous digital image analysis techniques have been developed with regard to transmission electron microscopy (TEM) with the help of programming. DigitalMicrograph (DM, Gatan Inc., USA), which is installed on most TEMs as operational software, includes a script language to develop customized software for image analysis. Based on the DM script language, this work provides a script source listing for quantitative strain measurements based on a geometric phase analysis.

• Applied Microscopy
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• v.45 no.3
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• pp.150-154
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• 2015

Negative staining electron microscopy facilitates the visualization of small bio-materials such as proteins; thus, many electron microscopists have used this conventional method to visualize the morphologies and structures of biological materials. To achieve sufficient contrast of the materials, a number of imaging parameters must be considered. Here, we examined the effects of one of the fundamental imaging parameters, electron beam exposure time, on electron densities generated using transmission electron microscopy. A single site of a negatively stained biological sample was illuminated with the electron beam for different times (1, 2, or 4 seconds) and sets of micrographs were collected. Computational image processing demonstrated that longer exposure times provide better electron densities at the molecular level. This report describes technical procedures for testing parameters that allow enhanced evaluations of the densities of electron microscopy images.

• Journal of radiological science and technology
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• v.46 no.3
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• pp.207-217
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• 2023

Image noise reduction algorithm performs important functions in light microscopy. This study aims to systematically review the research trend of types and performance evaluation methods of noise reduction algorithm in light microscopic images. A systematic literature search of three databases of publications from January 1985 to May 2020 was conducted; of the 139 publications reviewed, 16 were included in this study. For each research result, the subjects were categorized into four major frameworks-1. noise reduction method, 2. imaging technique, 3. imaging type, and 4. evaluation method-and analyzed. Since 2003, related studies have been conducted and published, and the number of papers has increased over the years and begun to decrease since 2016. The most commonly used method of noise reduction algorithm for light microscopy images was wavelet-transform-based technology, which was mostly applied in basic systems. In addition, research on the real experimental image was performed more actively than on the simulation condition, with the main case being to use the comparison parameter as an evaluation method. This systematic review is expected to be extremely useful in the future method of numerically analyzing the noise reduction efficiency of light microscopy images.

• Journal of Powder Materials
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• v.24 no.4
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• pp.285-291
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• 2017

We propose a custom analysis technique for the dark field (DF) image based on transmission electron microscopy (TEM). The custom analysis technique is developed based on the $DigitalMicrograph^{(R)}$ (DM) script language embedded in the Gatan digital microscopy software, which is used as the operational software for most TEM instruments. The developed software automatically scans an electron beam across a TEM sample and records a series of electron diffraction patterns. The recorded electron diffraction patterns provide DF and ADF images based on digital image processing. An experimental electron diffraction pattern is recorded from a IrMn polycrystal consisting of fine nanograins in order to test the proposed software. We demonstrate that the developed image processing technique well resolves nanograins of ~ 5 nm in diameter.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.