• Investigative Magnetic Resonance Imaging
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• v.11 no.2
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• pp.110-118
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• 2007

Purpose: The objective of this work to construct eigenvalue maps that have information of magnitude of three primary diffusion directions using diffusion tensor images. Materials and Methods: To construct eigenvalue maps, we used a 3.0T MRI scanner. We also compared the Moore-Penrose pseudo-inverse matrix method and the SVD (single value decomposition) method to calculate magnitude of three primary diffusion directions. Eigenvalue maps were constructed by calculating of magnitude of three primary diffusion directions. We did investigate the relationship between eigenvalue maps and fractional anisotropy map. Results: Using Diffusion Tensor Images by diffusion tensor imaging sequence, we did construct eigenvalue maps of three primary diffusion directions. Comparison between eigenvalue maps and Fractional Anisotropy map shows what is difference of Fractional Anisotropy value in brain anatomy. Furthermore, through the simulation of variable eigenvalues, we confirmed changes of Fractional Anisotropy values by variable eigenvalues. And Fractional anisotropy was not determined by magnitude of each primary diffusion direction, but it was determined by combination of each primary diffusion direction. Conclusion: By construction of eigenvalue maps, we can confirm what is the reason of fractional anisotropy variation by measurement the magnitude of three primary diffusion directions on lesion of brain white matter, using eigenvalue maps and fractional anisotropy map.

• Journal of the Korean Society of Radiology
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• v.2 no.2
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• pp.31-38
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• 2008

Line scan diffusion weighted imaging (LSDI) pulse sequence for 0.32 T magnetic resonance imaging (MRI) system was developed. In the LSDI pulse sequence, the imaging volume is formed by the intersection of the two perpendicular planes selected by the two slice-selective $\pi$/2-pulse and $\pi$-pulse and two diffusion sensitizing gradients placed on the both side of the refocusing $\pi$-pulse and the standard frequency encoding readout was followed. Since the maximum gradient amplitude for the MR system was 15 mT/m the maximum b value was $301.50s/mm^2$. Using the developed LSDI pulse sequence, the diffusion weighted images for the aqueous NaCl solution phantom and triacylglycerol solution phantom calculated from the line scan diffusion weighted images gives the same results within the standard error range (mean diffusivities = $963.90{\pm}79.83({\times}10^{-6}mm^2/s)$ at 0.32 T, $956.77{\pm}4.12({\times}10^{-6}mm^2/s)$ at 1.5 T) and the LSDI images were insensitive to the magnetic susceptibility difference and chemical shift.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.149-158
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• 2017

Fine temporal and spatial resolution of image data are necessary to monitor the phenology of vegetation. However, there is no single sensor provides fine temporal and spatial resolution. For solve this limitation, researches on spatiotemporal data fusion methods are being conducted. Among them, FSDAF (Flexible spatiotemporal data fusion) can fuse each band in high accuracy.In thisstudy, we applied MODIS NDVI and Landsat NDVI to enhance time resolution of NDVI based on FSDAF algorithm. Then we proposed the possibility of utilization in vegetation phenology monitoring. As a result of FSDAF method, the predicted NDVI from January to December well reflect the seasonal characteristics of broadleaf forest, evergreen forest and farmland. The RMSE values between predicted NDVI and actual NDVI (Landsat NDVI) of August and October were 0.049 and 0.085, and the correlation coefficients were 0.765 and 0.642 respectively. Spatiotemporal data fusion method is a pixel-based fusion technique that can be applied to variousspatial resolution images, and expected to be applied to various vegetation-related studies.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.6
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• pp.1-9
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• 2007

Recently, as a number of media are fused into a phone, the requirement of security of service provided on a mobile phone is increasing. For this, conventional cryptographic key based on password and security card is used in the mobile phone, but it has the characteristics which is easy to be vulnerable and to be illegally stolen. To overcome such a problem, the researches to generate key based on biometrics have been done. However, it has also the problem that biometric information is susceptible to the variation of environment, whereas conventional cryptographic system should generate invariant cryptographic key at any time. So, we propose new method of producing cryptographic key based on "Biometric matching-based key release" instead of "Biometric-based key generation" by using both face and iris information in order to overcome the unstability of uni-modal biometries. Also, by using mega-pixel camera embedded on mobile phone, we can provide users with convenience that both face and iris recognition is possible at the same time. Experimental results showed that we could obtain the EER(Equal Error Rate) performance of 0.5% when producing cryptographic key. And FAR was shown as about 0.002% in case of FRR of 25%. In addition, our system can provide the functionality of controlling FAR and FRR based on threshold.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.679-685
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• 2017

Computed tomography has widely been used to diagnose patient disease, and patient dose also increase rapidly. To reduce the patient dose by CT, various techniques have been applied. The iterative reconstruction is used in view of image reconstruction. Image quality of the reconstructed section image through algebraic reconstruction technique, one of iterative reconstruction methods, was examined by the normalized root mean square error. The computer program was written with the Visual C++ under the parallel beam geometry, Shepp-Logan head phantom of $512{\times}512$ size, projections of 360, and detector-pixels of 1,024. The forward and backward projection was realized by Joseph method. The minimum NRMS of 0.108 was obtained after 10 iterations in the regularization parameter of 0.09-0.12, and the optimum image was obtained after 8 and 6 iterations for 0.1% and 0.2% noise. Variation of optimum value of the regularization parameter was observed according to the phantom used. If the ART was used in the reconstruction, the optimal value of the regularization parameter should be found in the case-by-case. By finding the optimal regularization parameter in the algebraic reconstruction technique, the reconstruction time can be reduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.375-382
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• 2016

In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.1-8
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• 2003

In this paper, performance of the CPC(complex phase code) which is recently proposed as a practical phase encoding method for phase-code multiplexes holographic memory system is comparatively analyzed with those of the conventional phase codes such as PR(pure random code), RCE(random code with equality), WHM(Walsh Hadamard Matrix). In computer simulation, the size of an address bean is fixed at 32$\times$32 pixels and 0%-25% phase-error ratio in a pixel are intentionally added to the real phase values to consider the nonlinear phase-modulation characteristics of the practical spatial light modulator. From comparative analysis of crosstalks and signal-to-noise ratios for these phase codes by calculating auto-correlation and cross-correlation, it is found that the CPC have the lowest cross-correlation mean value of 0.021, the lowest standard deviation of 0.0113 and the highest signal-to-noise ratio(SNR) of 27.4 among the four types of phase code. In addition, from the calculation of the number of all possible address beams for these four types of phase code as the size of the address beam is fixed to 3232 pixels, the CPC is found to have 6.334$\times$10$^{49}$ address beams, which are relatively higher number than that of the conventional phase codes.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.210-218
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• 2002

This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.985-991
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• 2023

A tissue-equivalent phantom is necessary for quality control of hyperthermia therapy. However, since there is no phantom for this purpose, phantoms made from agar are being used in various studies. The tissue-equivalent properties of the agar phantom were confirmed by comparison with the tissue-equivalent material bolus in this study. CT images of the agar phantom and bolus were acquired, and tissue equivalent characteristics were analyzed with image analysis and dose calculation using a computerized radiation therapy planning system. The average pixel value was 96.960±10.999 in bolus, 108.559±8.233 in 3% agar phantom, and 111.844±8.651 in 4% agar phantom. Using the SSD technique, 100 cGy was prescribed at a depth of 1.5 cm and 6 MV X -ray was set to irradiated to 10x10 cm2, and the absorbed dose according to depth was calculated from the central axis of the beam. The intraclass correlation coefficient of dose distribution of bolus, 3% agar phantom, and 4% agar phantom was 0.979 (p<.001, 95%CI .957-.991). The density (g/cm3) at the point where the absorbed dose was calculated was 0.990±0.020 at the bolus, 1.018±0.020 at the 3% agar phantom, and 1.035±0.024 at the 4% agar phantom. In this study, the internal density distribution and uniformity of the agar phantom were confirmed to be appropriate as a tissue equivalent material by analysis of CT images and a computerized radiation therapy planning system.