• Investigative Magnetic Resonance Imaging
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• v.18 no.4
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• pp.303-313
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• 2014

Purpose : In-vivo conductivity reconstruction using transmit field ($B_1{^+}$) information of MRI was proposed. We assessed the accuracy of conductivity reconstruction in the presence of statistical noise in complex $B_1{^+}$ map and provided a parametric model of the conductivity-to-noise ratio value. Materials and Methods: The $B_1{^+}$ distribution was simulated for a cylindrical phantom model. By adding complex Gaussian noise to the simulated $B_1{^+}$ map, quantitative conductivity estimation error was evaluated. The quantitative evaluation process was repeated over several different parameters such as Larmor frequency, object radius and SNR of $B_1{^+}$ map. A parametric model for the conductivity-to-noise ratio was developed according to these various parameters. Results: According to the simulation results, conductivity estimation is more sensitive to statistical noise in $B_1{^+}$ phase than to noise in $B_1{^+}$ magnitude. The conductivity estimate of the object of interest does not depend on the external object surrounding it. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the $B_1{^+}$ map, Larmor frequency, the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targeted tissue, SNR of $B_1{^+}$ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. Conclusion: Through all these relationships, quantitative conductivity estimation error due to statistical noise in $B_1{^+}$ map is modeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.160-174
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• 2014

The purpose of this paper is to develop a meso-scale grid-based continuous hydrological model and apply to assess the future watershed hydrology by climate change. The model divides the watershed into rectangular cells, and the cell profile is divided into three layered flow components: a surface layer, a subsurface unsaturated layer, and a saturated layer. Soil water balance is calculated for each grid cell of the watershed, and updated daily time step. Evapotranspiration(ET) is calculated by Penman-Monteith method and the surface and subsurface flow adopts lag coefficients for multiple days contribution and recession curve slope for stream discharge. The model was calibrated and verified using 9 years(2001-2009) dam inflow data of two watersheds(Chungju Dam and Soyanggang Dam) with 1km spatial resolution. The average Nash-Sutcliffe model efficiency was 0.57 and 0.71, and the average determination coefficient was 0.65 and 0.72 respectively. For the whole Han river basin, the model was applied to assess the future climate change impact on the river bsain. Five IPCC SRES A1B scenarios of CSIRO MK3, GFDL CM2_1, CONS ECHO-G, MRI CGCM2_3_2, UKMO HADGEMI) showed the results of 7.0%~27.1 increase of runoff and the increase of evapotranspiration with both integrated and distributed model outputs.

• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.154-161
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• 1997

Purpose: Traumatic rupture of the diaphragm is not easy to diagnose and often delayed. Delayed diagnosis of diaphragmatic rupture accompanied by higher chances of strangulation of herniated viscera which may result in higher morbility and mortality. The purpose of this study was to evaluate diagnostic accuracy of spiral CT, MRI and US for the diagnosis of diaphragmatic rupture in an animal model. Materials and Methods: Small, medium, and large sized transabdominal diaphragmatic ruptures were surgically made in experimental rabbits and then followed up with spiral CT, MR!, and US at 1 day, 3 day, and 1 week after operation. Results: US was superior to MR! or spiral CT in diagnosis of diaphragmatic rupture(P(0.05). The sensitivity and specificity were 94.4% and 92.9% for US, 54.0% and 85.7% for MRI, and 46.0% and 78.6% for spiral CT, respectively. The size of laceration was not related to diagnostic sensitivity in US. Sensitivity of MRI and spiral CT increased as the size of laceration were larger, but no statistical significance was present(P>0.05). All experimental animals developed pleural effusion or hemothorax one day after operation. In acute phase, US and MRI were more sensitive than spiral CT in detecting diaphragmatic rupture. Spiral CT was more sensitive than US and MRI in delayed phase but without statistical significance(P>0.05). In the experimental rabbits with accompanying visceral hernia through the diaphragmatic defect, diagnostic accuracy was found equally high among three image modalities(P>0.05). Conclusion: This study indicates that US is the most accurate diagnostic method in detecting injury to the diaphragm in a rabbit model. The findings obtained in this experimental study can be applied to the diaphragmatic rupture of human being.

• Investigative Magnetic Resonance Imaging
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• v.11 no.1
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• pp.20-26
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• 2007

Purpose : The purpose of the present study was to develop and optimize solenoid coil for animal- model in 3 T MRI system and investigate and compare with the birdcage coil concerning the image quality with the various parameters such as SNR and Q-factor. Materials and Methods : Solenoid coil for animal-model was made on the acryl structure (diameter 4 cm, length 10 cm) 3 times-winding cooper tape of width 2 cm, thickness 0.05 cm and length 10 cm with 2 cm interval between winded tapes. Capacitors from 2 pF to 100 pF were used, and the solenoid coil was designed for receiver only coil. Results : SNR of the developed solenoid was 985 in CuSO4 0.7 g/L and 995 in rat experiment. Q-factor was 84-89 in unloaded condition and 203-206 in loaded condition. Conclusion : The resolution of the image obtained from solenoid was relatively higher than that of the conventional birdcage coil. In addition, the homogeneity of RF field by coil simulation was significantly excellent. The present study demonstrated that the solenoid coil could be useful to obtain small animal images with better contrast, resolution, visibility than images from birdcage.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.259-266
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• 2013

Purpose : To investigate the blood pharmacokinetics and bio-distribution of DTPA-bis-amide (L3) Gd(III) complexes. Materials and Methods: The pharmacokinetics and bio-distribution of Gd $(L3)(H_2O){\cdot}nH_2O$ were investigated in Sprague-Dawley rats after intravenous administration at a dose of 0.1 mmol Gd/kg. The Gd content in the blood, various tissues, and organs was determined by ICP-AES. Blood pharmacokinetic parameters were calculated using a two-compartment model. Results: The half-lives of ${\alpha}$ phase and ${\beta}$ phase Gd $(L3)(H_2O){\cdot}nH_2O$ were $2.286{\pm}0.11$ min and $146.1{\pm}7.5$ min, respectively. The bio-distribution properties reveal that the complex is mainly excreted by the renal pathway, and possibly excreted by the hepatobiliary route. The concentration ratio of Gd (III) was significantly higher in the liver and spleen than in other organs, and small amounts of Gd (III) ion were detected in the blood or other tissues of rats only after 7 days of intravenous administration. Conclusion: The MRI contrast agent Gd $(L3)(H_2O){\cdot}nH_2O$ provides prolonged blood pool retention in the circulation and then clears rapidly with minimal accumulation of Gd(III) ions. The synthesis of gadolinium complexes with well-balanced lipophilicity and hydrophilicity shows promise for their further development as blood pool MRI contrast agents.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.1-7
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• 2016

Structural MRI(sMRI) imaging is used to extract morphometric features after Grey Matter (GM), White Matter (WM) for several univariate and multivariate method, and Cerebro-spinal Fluid (CSF) segmentation. A new approach is applied for the diagnosis of very mild to mild AD. We propose the classification method of Alzheimer disease patients from normal controls by combining morphometric features and Gaussian Mixture Models parameters along with MMSE (Mini Mental State Examination) score. The combined features are fed into Multi-kernel SVM classifier after getting rid of curse of dimensionality using principal component analysis. The experimenral results of the proposed diagnosis method yield up to 96% stratification accuracy with Multi-kernel SVM along with high sensitivity and specificity above 90%.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.462-464
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• 2022

의료영상기반의 인공지능 연구는 질환의 조기진단 및 예측 분야에 눈부신 기술발전이 되어왔다. 장기 섬유증은 만성 염증성 질환의 질병 진행을 특징짓고 전 세계적으로 모든 원인으로 인한 사망률의 45%에 기여하며, 그중 간 섬유증은 주로 삶의 질과 예후를 결정한다. 해당 질환은 임상 현장에서 혈액데이터 분석 그리고 간생검을 통해 진단을 하고 있으나 최근 의료영상 분석을 통해 진단에 활용하고 있는 추세이다. 본 논문에서는 인공지능을 기반으로 하여, 간 섬유화를 진단하기 위해 MRI영상을 학습하여 질환에 대한 중증도 진단을 돕는 인공지능 모델을 제시하고자 한다. 이를 위해 인공지능 모델을 개발하는 과정과 그 결과를 보인다. 본 논문에서 제시한 모델을 통해 간 섬유화를 빠르게 진단할 수 있을 것으로 기대한다.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.77-77
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• 2003

CT와 MRI의 단면 영상을 대상으로 영상분할 (Image segmentation)과 Image registration방법을 이용하여 인체 모델을 개발 하고자 한다. 우선 인체의 Head와 Neck부분의 CT와 MR 영상을 얻어 뼈, 근육, 인대, 그리고 그 밖의 장기의 해부학적 영상 특징을 분석하였다. 인체의 Head와 Neck 부분에 대한 CT와 MR 영상에 대해 각 부위별로 ROI(region-of-interrest)를 설정하였고, 각 volxel 마다 3차원 좌표를 계산할 수 있는 소프트웨어를 개발하였다. 특히 각 해부학적 영상에서 부위별로 CT 번호를 분석하고, pulse sequence에 따른 MRI 영상의 부위별 특정을 분석하였다. 이 분석한 자료를 바탕으로 영상 분할을 하였다. 영상 분할전에 각종 잡음(noise) 제거 및 영상 분할을 효과적으로 처리하기 위해 기본적인 영상처리 (filtering)를 구현하였고, 대조도(contrast) 및 밝기(brightness)를 조절할 수 있게 프로그램을 구현하였다. 영상 분할 방법 중 선(line) 및 에지(edge) 의 검출 방법, 문턱치화(threshold) 방법, 영역확대(region growing) 방법으로 영상 분할을 해봄으로써 우리의 인체 모델링 개발에 가장 적합한 영상 분할 알고리듬 방법을 찾도록 시도하였다. 결과적으로 말하면, 한가지 방법의 알고리듬을 쓰는 것보다는 인체의 부위에 따라 두 가지 이상의 알고리듬 방법을 쓰는 것이 원하고자 하는 부위를 영상 분할하는데 더 효과적이다는 것을 알게 되었다. 우리의 연구 과제에서는 영역확대(region growing) 방법과 문턱치화 방법, 모드법(피크니스, 밸리)의 알고리듬을 이용하여 영상 분할을 한 결과 우리가 얻고자 하는 인체 부위별 중 근육과 뼈를 구별하는데는 별 무리가 없었으나, 인대 및 기타 장기를 구별하는데는 어려움을 겪게 되었다. 이후에 좀더 알고리듬을 연구하여 이번 연구에서 구별하기 어려운 장기 부분도 구별 할 수 있도록 노력하겠다.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.116-118
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• 1997

In hippocampal morphology Abnormalities, including unilateral or bilateral volume loss, are known to occur in epilepsy, Alzheimer's disease, and in certain amnestic syndromes. To detect such abnormalities in hippocampal morphology, we present a method that combines region growing and dynamic contour model to detect hippocampus from MRI brain data. The segmentation process is performed two steps. First region growing with a seed point is performed in the region of hippocampus and the initial contour of dynamic contour model is obtained. Second, the initial contour is modified on the basis of criteria that integrate energy with contour smoothness and the image gradient along the contour. As a result, this method improves fairly sensitivity to the choice of the initial seed point, which is often seen by conventional contour model. The power and practicality of this method have been tested on two brain datasets. Thus, we have developed an effective algorithm to extract hippocampus from MRI brain data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.776-787
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• 1998

This paper analyzes the local specific absorption rates (SAR's) averaged over 1 g and 10 g in a human head model in contact with a mobile phone operating at 835 MHz. The used numerical method is a total field finite-difference time-domain (FDTD) technique. The phone was simulated with a conducting box, a plastic case, and a whip antennal composed of a monopole and a helix. The discrete human model of the spatial resolution 3 mm is based on Magnetic Resonance Imaging (MRI), computerized tomography (CT) and anatomical images. The near field and far field and far field patterns were analyzed for extended and retracted phone. The two methods to take the volumes of the weights, 1 g or 10 g in tissue are proposed and compared to offer a reproductive technique for SAR estimations.