• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1058-1062
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• 2008

지구 온난화에 의한 대기 순환의 변화와 이에 따른 수증기 수송 및 강수량의 변화는 전지구 및 지역적인 수문환경의 변화를 초래하므로 장기적인 차원의 수자원 계획 수립에는 반드시 기후 변화에 따른 영향이 제대로 반영되어야 한다. 그러나 개별 모델이 사용하는 역학과정과 물리과정의 모수화 및 분해능이 다르고 이에 따른 모의 결과도 다르게 나타나는 등의 상당한 불확실성이 내재되어 있다. 따라서 본 연구에서는 기후변화에 관한 정부간 패널인 IPCC(Intergovernmental Panel on Climate Change)에 참여한 대기해양결합 대순환모델(AOGCMs)이 온실가스 배출 시나리오를 바탕으로 생산한 기온과 강수의 불확실성을 동아시아에 대해 평가하고 이를 바탕으로 미래 기후를 전망하였다. 국립기상연구소 ECHO-G/S 모델과 IPCC 23개 모델의 배출 시나리오(Special Report on Emissions Scenarios, SRES) 자료는 20세기(1900-1999년)와 21세기(2000-2099년)의 200년 동안이고, 관측자료는 영국 CRU(Climate Research Unit) 월평균 2m 기온의 30년(1961-1990년) 평균값과 CMAP 월 평균 강수량의 21년간(1979-1990년) 평균값을 이용하였다. 동아시아지역 기온과 강수의 불확실성을 평가하기 위해서 모델과 관측간 편이, 평균제곱근오차(RMSE) 등의 통계적인 방법을 사용하였다. 동아시아 지역의 연평균 기온은 대체로 모델의 기온이 관측보다 적게 모의되는 음의 편이를 나타내고, 강수는 모델이 관측보다 더 크게 모의 되는 양의 편이를 나타냈다. 계절적으로는 여름철 강수와 봄철 기온의 편이가 크게 나타났다. 연평균 및 겨울철 강수와 기온의 RMSE는 비례하는데 이는 기온 모의성능이 좋은 모델이 강수 모의성능도 좋게 나타나는 것을 의미한다.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.469-475
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• 2009

Diseases caused by indurate tissues of the internal organs are liver cirrhosis and abdominal sclerosis. The cause of chronic gastro-intestinal disease is a digestive system disorder and a defecation disorder. They impede peristaltic movement and digestive system with the symptom that indurate tissues. The purpose of the present study was to determine the disease grade quantitatively by measuring an indurated standard of tissues and organs. For the measurement of elasticity, we designed the system that measure the displacement of the substance and approved pressure using ultrasound transducer. For verification of developed system, we compared elasticity as results of experiment between the developed system and public elasticity measurement machine at individual plastic phantoms made by plastic hardener and softener. Elasticity of the plastic phantoms is averagely 0.007MPa lower measured by developed system than Micro-indenter, and less than 10% errors. Comparing with economical value and accuracy between developed system and Micro-indenter, the system is significant of measurement for tissue elasticity. Thus, it is possible to measure a elasticity at human tissue and organ. A chronic gastro-disease as well as grade could be decided objective validity using this system.

• 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.

• Journal of Biomedical Engineering Research
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• v.23 no.4
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• pp.269-279
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• 2002

When we inject a current into an electrically conducting subject such as a human body, voltage and current density distributions are formed inside the subject. The current density within the subject and injection current in the lead wires generate a magnetic field. This magnetic flux density within the subject distorts phase of spin-echo magnetic resonance images. In Magnetic Resonance Current Density Imaging (MRCDI) technique, we obtain internal magnetic flux density images and produce current density images from $\bigtriangledown{\times}B/\mu_\theta$. This internal information is used in Magnetic Resonance Electrical Impedance Tomography (MREIT) where we try to reconstruct a cross-sectional resistivity image of a subject. This paper describes numerical techniques of computing voltage. current density, and magnetic flux density within a subject due to an injection current. We use the Finite Element Method (FEM) and Biot-Savart law to calculate these variables from three-dimensional models with different internal resistivity distributions. The numerical analysis techniques described in this paper are used in the design of MRCDI experiments and also image reconstruction a1gorithms for MREIT.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.245-250
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• 2011

Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.133-133
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• 2002

Purpose： The purpose of paper is to implement software to visualize brain fiber tract using a 24-bit color coding scheme and to test its feasibility. Materials and Methods： MR imaging was performed on GE 1.5 T Signa scanner. For diffusion tensor image, we used a single shot spin-echo EPI sequence with 7 non-colinear pulsed-field gradient directions： (x, y, z)：(1,1,0),(-1,1,0),(1,0,1),(-1,0,1),(0,1,1),(0,1,-1) and without diffusion gradient. B-factor was 500 sec/$\textrm{mm}^2$. Acquisition parameters are as follows： TUTE=10000ms/99ms, FOV=240mm, matrix=128${\times}$128, slice thickness/gap=6mm/0mm, total slice number=30. Subjects consisted of 10 normal young volunteers (age：21∼26 yrs, 5 men, 5 women). All DTI images were smoothed with Gaussian kernel with the FWHM of 2 pixels. Color coding schemes for visualization of directional information was as follows. HSV(Hue, Saturation, Value) color system is appropriate for assigning RGB(Red, Green, and Blue) value for every different directions because of its volumetric directional expression. Each of HSV are assigned due to (r,$\theta$,${\Phi}$) in spherical coordinate. HSV calculated by this way can be transformed into RGB color system by general HSV to RGB conversion formula. Symmetry schemes： It is natural to code the antipodal direction to be same color(antipodal symmetry). So even with no symmetry scheme, the antipodal symmetry must be included. With no symmetry scheme, we can assign every different colors for every different orientation.(H =${\Phi}$, S=2$\theta$/$\pi$, V=λw, where λw is anisotropy). But that may assign very discontinuous color even between adjacent yokels. On the other hand, Full symmetry or absolute value scheme includes symmetry for 180$^{\circ}$ rotation about xy-plane of color coordinate (rotational symmetry) and for both hemisphere (mirror symmetry). In absolute value scheme, each of RGB value can be expressed as follows. R=λw｜Vx｜, G=λw｜Vy｜, B=λw｜Vz｜, where (Vx, Vy, Vz) is eigenvector corresponding to the largest eigenvalue of diffusion tensor. With applying full symmetry or absolute value scheme, we can get more continuous color coding at the expense of coding same color for symmetric direction. For better visualization of fiber tract directions, Gamma and brightness correction had done. All of these implementations were done on the IDL 5.4 platform.