• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.547-555
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• 2019

The purpose of this study was to evaluate the usefulness of routine liver ultrasonography on the basis of the scoring system according to the morphological parameters of liver ultrasound images and the histopathological results of liver biopsy. The morphological parameters of the liver through ultrasonography were divided into liver surface, liver edge and liver parenchyma. Pathologic results of liver biopsy were classified as mild fibrosis(F1), significant fibrosis(F2), severe fibrosis(F3), and cirrhosis(F4). In conclusion, routine ultrasound examination showed a sensitive predictive factor for fibrosis with mild fibrosis (F1) to severe fibrosis (F3) were liver edge>liver parenchyma>liver surface. However, the predictive factors for detecting cirrhosis (F4) were liver parenchyma>liver surface>liver edge. The use of three variable combinations rather than individual variables in routine ultrasonography may be useful in evaluating the degree and progress of liver fibrosis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.255-258
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• 2008

For rapidly increasing amount of medical images, it is difficult for radiologist to interpretate the medical images fastly and for sufficient time. We investigated whether liver CT image has good features to be analyzed by computer algorithm, We examed the CT images of liver tumors (Hepetocellular carcinomas; HCCs) and searched any potential morphologic characteristics to be analyzed by computer algorithms. On unenhanced CT, HCCs appeared hypodense After enhancement, most HCCs were hyperdense, and then. as a consequence of rapid washout, HCCS became hypodense compared with the liver parenchyma. Most CT images of HCCs showed synchronous phase-specific.morphologic features. We applied various edge detection filters to these images and some filters showed favorable performance in the detection of tile edge of liver and HCC. Therefore, theses features seems to be analyzed by computer algorithms effectively.Further studies may be warranted.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.89-90
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• 2019

본 논문에서는 ultrasound image Right Parasagittal Liver에 edge detection을 적용한 후, 특징점 검출 알고리즘인 Scale Invarient Feature Transfom(SIFT)를 이용하여 특징점의 위치를 살펴보도록 한다. edge detection 알고리즘으로는 Canny edge detection과 Prewitt edge detection을 적용하기로 한다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.51-57
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• 2012

Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.16-37
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• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.

• The Korean Journal of Nuclear Medicine
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• v.22 no.2
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• pp.181-185
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• 1988

Since hepatocyte clearance, leading edge parencymal transit time and biliary excretion can be evaluated separately with hepatobiliary scan using $^{99m}Tc-DISIDA$, hepatobiliary scan may be useful in differentiating intrahepatic cholestasis from extrahepatic cholestasis. Excretory liver function was analysed in 13 healthy subjects and 11 patients with clinically suspected hepatocellular disease and 9 patients with extrahepatic biliary obstruction confirmed by surgery, radiological and clinical evidence. Indices of total liver activity (% TLA), liver parechymal uptake (% LPU), heart pool clearance (% HPC) and liver-heart rate (% LHR) were calculated from time activity curve over heart and liver. Compared with healthy subjects, significant reduction (p<0.05) in total liver activity (% TLA) and liver-heart rate (% LHR) was observed in all patients group. But no useful indices was demonstrated in differentiating hepatocellular disease from extrahepatic biliary obstruction.

• Journal of radiological science and technology
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• v.42 no.3
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• pp.187-194
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• 2019

The purpose of this study was to evaluate the pathologic results of hepatic parenchyma parameters such as liver parenchyma, liver surface, liver margin and liver, portal vein, spleen size, And to evaluate the usefulness of fibrosis progression and hepatic ultrasonography. The sensitivity, specificity, positive predictive value, and prognostic value according to the stage of fibrosis and grade of inflammation were divided into two groups according to the morphologic variable "A" through ultrasound and "B" We evaluated the predictive value and predicted the variables to evaluate fibrosis in clinical diagnosis and treatment of patients with chronic liver disease. The sensitivity and specificity of hepatic fibrosis in hepatic morphologic variables and other size variables were highest in liver surface and edge. The morphologic parameters used in the evaluation of fibrosis were clinically relevant in distinguishing the fibrosis stage from the results of liver biopsy.

• Investigative Magnetic Resonance Imaging
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• v.21 no.2
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• pp.71-81
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• 2017

Purpose: To compare three, motion-resistant, T1-weighted MR sequences on the hepatobiliary phase for gadoxetic acid-enhanced MR imaging of the liver. Materials and Methods: In this retrospective study, 79 patients underwent gadoxetic acid-enhanced, 3T liver MR imaging. Fifty-nine were examined using a standard protocol, and 20 were examined using a motion-resistant protocol. During the hepatocyte-specific phase, three MR sequences were acquired: 1) gradient recalled echo (GRE) with controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA); 2) radial GRE with the interleaved angle-bisection scheme (ILAB); and 3) radial GRE with golden-angle scheme (GA). Two readers independently assessed images with motion artifacts, streaking artifacts, liver-edge sharpness, hepatic vessel clarity, lesion conspicuity, and overall image quality, using a 5-point scale. The images were assessed by measurement of liver signal-to-noise ratio (SNR), and tumor-to-liver contrast-to-noise ratio (CNR). The results were compared, using repeated post-hoc, paired t-tests with Bonferroni correction and the Wilcoxon signed rank test with Bonferroni correction. Results: In the qualitative analysis of cooperative patients, the results for CAIPIRINHA had significantly higher ratings for streak artifacts, liver-edge sharpness, hepatic vessel clarity, and overall image quality as compared to, radial GRE, (P < 0.016). In the imaging of uncooperative patients, higher scores were recorded for ILAB and GA with respect to all of the qualitative assessments, except for streak artifact, compared with CAIPIRINHA (P < 0.016). However, no significant differences were found between ILAB and GA. For quantitative analysis in uncooperative patients, the mean liver SNR and lesion-to-liver CNR with radial GRE were significantly higher than those of CAIPIRINHA (P < 0.016). Conclusion: In uncooperative patients, the use of the radial GRE sequence can improve the image quality compared to GRE imaging with CAIPIRINHA, despite the data acquisition methods used. The GRE imaging with CAIPIRINHA is applicable for patients without breath-holding difficulties.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.419-422
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• 2014

본 논문에서는 환자와 검사자에게 초음파 영상의 객관화된 정보를 정확하게 제공하기 위해 간과 신장의 초음파 영상에 SOM 기법을 적용하여 지방간 농도 수치를 분류하는 방법을 제시한다. 제안된 방법은 간, 신장 영역을 촬영한 초음파 영상에서 촬영정보나 눈금자 등과 같이 필요 없는 부분을 잡음으로 간주하여 제거한 Region Of Interest(ROI) 영상을 추출하고, 추출된 ROI 영상에서 명암대비를 강조하기 위해 Fuzzy Stretching 기법을 적용한다. Stretching된 영상에 Enhanced Average Binary와 Labeling 기법으로 적용하여 얻은 Contour 정보를 분석하여 잡음을 제거한 후, 지방간의 측정 영역을 추출한다. 추출된 간과 신장의 측정 영역에 SOM 기법을 적용하여 명암도 값을 분류한 후, 간과 신장의 실질 영역의 대표 명암도를 각각 추출하여 비교 분석한다. 제안된 방법을 초음파 영상에 적용한 결과, 효율적이고 객관적으로 간의 지방도를 분류할 수 있는 가능성을 확인하였다.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.911-917
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• 2023

The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.