• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2521-2526
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• 2015

Objective: The purpose of this study was to evaluate computed tomography (CT) virtual non-contrast (VNC) spectral imaging for gastric carcinoma. Materials and Methods: Fifty-two patients with histologically proven gastric carcinomas underwent gemstone spectral imaging (GSI) including non-contrast and contrast-enhanced hepatic arterial, portal venous, and equilibrium phase acquisitions prior to surgery. VNC arterial phase (VNCa), VNC venous phase (VNCv), and VNC equilibrium phase (VNCe) images were obtained by subtracting iodine from iodine/water images. Images were analyzed with respect to image quality, gastric carcinoma-intragastric water contrast-to-noise ratio (CNR), gastric carcinoma-perigastric fat CNR, serosal invasion, and enlarged lymph nodes around the lesions. Results: Carcinoma-water CNR values were significantly higher in VNCa, VNCv, and VNCe images than in normal CT images (2.72, 2.60, 2.61, respectively, vs 2.35, $p{\leq}0.008$). Carcinoma-perigastric fat CNR values were significantly lower in VNCa, VNCv, and VNCe images than in normal CT images (7.63, 7.49, 7.32, respectively, vs 8.48, p< 0.001). There were no significant differences of carcinoma-water CNR and carcinoma-perigastric fat CNR among VNCa, VNCv, and VNCe images. There was no difference in the determination of invasion or enlarged lymph nodes between normal CT and VNCa images. Conclusions: VNC arterial phase images may be a surrogate for conventional non-contrast CT images in gastric carcinoma evaluation.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.369-378
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• 2018

Purpose: The aim of this study was to construct a saponin content-predicting model using shortwave infrared imaging spectroscopy. Methods: The experiment used a shortwave imaging spectrometer and ENVI spectral acquisition software sampling a spectrum of 910 nm-2500 nm. The corresponding preprocessing and mathematical modeling analysis was performed by Unscrambler 9.7 software to establish a ginsenoside nondestructive spectral testing prediction model. Results: The optimal preprocessing method was determined to be a standard normal variable transformation combined with the second-order differential method. The coefficient of determination, $R^2$, of the mathematical model established by the partial least squares method was found to be 0.9999, while the root mean squared error of prediction, RMSEP, was found to be 0.0043, and root mean squared error of calibration, RMSEC, was 0.0041. The residuals of the majority of the samples used for the prediction were between ${\pm}1$. Conclusion: The experiment showed that the predicted model featured a high correlation with real values and a good prediction result, such that this technique can be appropriately applied for the nondestructive testing of ginseng quality.

• Journal of Astronomy and Space Sciences
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• v.41 no.2
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• pp.121-138
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• 2024

Advances in solar-terrestrial physics are generally linked to the development of innovative new sensor technologies, affording us ever better sensitivity, higher resolution, and broader spectral response. Recent advances in low-noise InGaAs sensor technology have enabled the realization of low-light-level scientific imaging within the short-wave infrared (SWIR) region of the electromagnetic spectrum. This paper describes a new and highly sensitive ultra-wide angle imager that offers an expansion of auroral and airglow imaging capabilities into the SWIR spectral range of 900-1,700 nm. The imager has already proven successful in large-area remote sensing of mesospheric temperatures and in providing intensity maps showing the propagation and dissipation of atmospheric gravity waves and ripples. The addition of an automated filter wheel expands the range of applications of an already versatile SWIR detector. Several potential applications are proposed herein, with an emphasis on auroral science. The combined data from this type of instrument and other existing instrumentation holds a strong potential to further enhance our understanding of the geospace environment.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1439-1444
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• 2015

Measuring spectral reflectance can be regarded as obtaining inherent color parameters, and spectral reflectance has been used in image processing. Model-based spectrum recovering, one of the method for obtaining spectral reflectance, uses ordinary camera with multiple illuminations. Conventional model-based methods allow to recover spectral reflectance efficiently by using only a few parameters, however it requires some parameters such as power spectrum of illuminations and spectrum sensitivity of camera. In this paper, we propose an enhanced model-based spectrum recovering method without pre-measured parameters: power spectrum of illuminations and spectrum sensitivity of camera. Instead of measuring each parameters, spectral reflectance can be efficiently recovered by estimating and using the spectrum characteristic matrix which contains spectrum parameters: basis function, power spectrum of illumination, and spectrum sensitivity of camera. The spectrum characteristic matrix can be easily estimated using captured images from scenes with color checker under multiple illuminations. Additionally, we suggest fast recovering method preserving positive constraint of spectrum by nonnegative basis function of spectral reflectance. Results of our method showed accurately reconstructed spectral reflectance and fast constrained estimation with unmeasured camera and illumination. As our method could be conducted conveniently, measuring spectral reflectance is expected to be widely used.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.10a
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• pp.85-108
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• 2004

• Proceedings of the KSMRM Conference
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• 2000.11a
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• pp.50-50
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• 2000

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.2
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• pp.232-240
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• 2013

This paper presents recent advances in damage visualization algorithms of laser generated ultrasonic propagation imaging(UPI) system. An effective damage evaluation method is required to extract correct information from raw data to properly characterize anomalies present in structure. A temporal-reference free imaging system provides easy and rapid defect inspection capability with less computational complexity. In this paper a number of methods such as ultrasonic wave propagation imaging(UWPI), anomalous wave propagation imaging(AWPI), ultrasonic spectral imaging(USI), wavelet ultrasonic propagation imaging(WUPI), variable time window amplitude mapping(VTWAM), time point adjustment(TPA), time of flight and amplitude mapping(ToF&Amp) and ultrasonic wavenumber imaging(UWI) are discussed with instances of successful implementation on various structures.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.29.2-29.2
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• 2010

The Extreme ultraviolet Imaging Spectrometer (EIS) on board Hinode provide us with excellent imaging spectroscopic data with very good spatial and spectral resolutions, which can be used for detecting Doppler flows in transition region and coronal lines as well as diagnosing plasma properties such as temperature, density, and non-thermal velocity. In this study we have made an EUV-imaging spectroscopic study of the source region of a partial halo coronal mass ejection (CME) that occurred on 2007 July 9 in NOAA 10961. Dopplergrams are obtained before and after the CME eruption using 12 EIS spectral lines (Log T= 4.9~7.2). Major results are summarized as follows. First, it is noted that either red shifts disappeared or blue shifts newly appeared for all spectral lines lower than Log T =6.0. Second, there were significant intensity increases for all wavelengths. Third, there were no significant variations in non-thermal motions for all wavelengths. We found one interesting bright point that newly appeared after the CME eruption. We discuss the implication on the results in terms of the CME eruption.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.561-565
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• 2011

This paper presents an imaging system for reconstruction of enhanced color images using the conventional Bayer CFA. By extracting various colors such as RGBCY from two sequential images which consist of a image by broadband G channel lens filter and the other image captured without one, the proposed color image reconstruction system can reduce the computational complexity for demosaicking and make high resolution color information without aliasing artifacts. Because the proposed system uses the common Bayer CFA image sensor, fabricating a new type of CFA is not necessary for obtaining a multi-spectral image, which can be easily extensible for applications of multi-spectral imaging. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing demosaicking methods, the proposed camera system showed the significant improvements in the sense of color resolution.

• Journal of the Korean earth science society
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• v.38 no.7
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• pp.535-545
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• 2017

Maritime accidents around the Korean Peninsula are increasing, and the ship detection research using remote sensing data is consequently becoming increasingly important. This study presented a new ship detection algorithm using hyperspectral images that provide the spectral information of several hundred channels in the ship detection field, which depends on high resolution optical imagery. We applied a spectral matching algorithm between the reflection spectrum of the ship deck obtained from two field observations and the ship and seawater spectrum of the hyperspectral sensor of an airborne visible/infrared imaging spectrometer. A total of five detection algorithms were used, namely spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), spectral angle mapper (SAM), and spectral information divergence (SID). SDS showed an error in the detection of seawater inside the ship, and SAM showed a clear classification result with a difference between ship and seawater of approximately 1.8 times. Additionally, the present study classified the vessels included in hyperspectral images by presenting the adaptive thresholds of each technique. As a result, SAM and SID showed superior ship detection abilities compared to those of other detection algorithms.