• 대한수의학회지
• /
• 제38권4호
• /
• pp.918-928
• /
• 1998

The present study was done with two aims. First, to evaluate the radiographic measurements of liver volumes in normal and hepatomegaly dogs induced by carbon tetrachloride. Second, to investigate quantitative tissue echo pattern by ultrasonography. Gray level histogram of the normal liver and the kidney were estimated with carbon tetra-chloride intoxication. In normal, r-square for liver volume to body weight was 0.93372, and this showed direct linear regression. Gray level histograms of the normal liver and the kidney were $19.150{\pm}2.490$(mean${\pm}$SD) and $13.175{\pm}2.686$(mean${\pm}$SD) respectively(p < 0.01). Liver parenchymal echogenicity was more hyperechogenic than kidney cortex echogenicity. Liver/Kidney ratio was $1.504{\pm}0.313$ and it can be used relative comparison of liver and kidney parenchymal echogenicity. In carbon-tetrachloride($CCl_4$) intoxication, changes of liver volume appeared to increase up to 24 hours after administration (p < 0.05), and decreased gradually to normal level after 2~5 days. Gray level histogram of liver parenchyma decreased up to 24hours (p < 0.01) after intoxication and then gradually increased to normal level. But that of kidney cortex had no significant change. Liver/Kidney ratio also decreased by 2 days(p < 0.01) and then gradually increased to normal level. On histopathologic features of hepatic tissues in carbon tetrachloride intoxication, both coagulative necrosis of hepatic cell and hemorrhage of centrilobular & midzonal area were identified. Conclusively, plain radiography is a useful diagnostic method for evaluating liver volume in mild hepatomegaly. Especially, it is considered that an adequate numerical processing of the liver length, depth and thoracic width and depth measurement would be helpful. Using gray level histogram, ultrasonographic evaluation was useful objective methods in early diagnosis of diffuse hepatic disease.

• 대한방사선치료학회지
• /
• 제26권1호
• /
• pp.1-9
• /
• 2014

목 적 : 간암 치료 시 호흡으로 인한 움직임을 최소화하기 위해 환자 체위 변화에서 종양의 움직임과 용적 변화를 분석하고자 하였다. 대상 및 방법 : 간 세포암종(Hepatocellular Carcinoma) 환자 14명의 환자를 대상으로 시행하였다. 바로 누운 자세(Supine position)와 엎드린 자세(Prone position)에서 2가지 방법으로 환자 고정기구를 제작하고 영상을 획득하여 간 종양의 움직임과 용적 그리고 선량을 분석하였다. 결 과 : 바로 누운 자세(Supine position)와 엎드린 자세(Prone position) 에서 표적의 왼쪽-오른쪽(LR, Left-right) 움직임은 평균 $2.76{\pm}1.25mm$, $2.21{\pm}0.93mm$이고, 앞-뒤(AP, Anterior-posterior)와 상하(SI. Superior-inferior) 방향의 움직임은 각각 $4.02{\pm}1.63mm$, $11.56{\pm}3.08mm$, $3.36{\pm}1.17mm$, $7.45{\pm}1.96mm$이었다. 이를 이용한 엎드린 자세(Prone position)에서 치료 용적(Treatment volume)은 감소하였고, 이에 따라 정상간 용적은 증가 하였다. 결 론 : 호흡에 의한 간의 움직임을 최소화함으로써 치료 용적(Treatment volume)의 경계여유를 감소시킬 수 있었다. 즉 환자 자세 변화 특히 엎드린(Prone) 자세는 간의 움직임을 감소 시켜주고 정상 간의 용적을 증가 시킬 수 있을 것으로 사료된다.

• 대한전자공학회논문지SP
• /
• 제47권1호
• /
• pp.17-24
• /
• 2010

본 논문은 생체간이식 전에 복부 MDCT(Multi-Detector Computed Tomography) 영상에서 이식편의 체적(the volume of right and left liver lobe)을 정확하게 계산하기 위하여 좌간과 우간을 나누는 방법을 제안하였다. 간이 추출된 영상에 해부학적인 좌간과 우간을 나누는 4점(하대정맥(Inferior Vena Cava)를 반으로 나눌 수 있는 중심점, 담낭와와 가까운 중간정맥(Middle Hepatic Vein)의 끝부분 한 점, 좌우문맥(Portal Vein) 분지부에서 한 점, 담낭와(gallbladder fossa)를 좌우로 나눌 수 있는 중심점)을 선택한다. 선택된 4점을 기준으로 좌간과 우간을 나누고 체적과 간 전체에 대한 좌우간의 비율을 계산한다. 계산된 체적의 정확성을 입증하기 위해 방사선과 의사가 수동으로 처리하여 계산한 체적과 함께 수술 중 획득한 실측무게와 비교하였다. 그리고 4점을 선택한 후 좌우간을 분할하여 체적을 계산하는 시간을 측정하여 수술실에서 실시간으로 처리 가능한 지의 여부를 확인하였다. 본 연구는 간이식에 참여하는 기증자와 수혜자의 안전을 보장하기 위하여 진행되었다.

• Korean Journal of Radiology
• /
• 제24권4호
• /
• pp.294-304
• /
• 2023

Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). Conclusion: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.

• 대한한방내과학회지
• /
• 제28권1호
• /
• pp.115-123
• /
• 2007

Objectives : To investigate the correlations among alcohol consumption, alcoholic liver disorders, physical symptoms, and behaviors in heavy drinkers. Methods : 53 males who self-realized their severe alcohol consumption were enrolled in this study. 10 answers for a questionnaire, serum parameter, sonographic finding and body mass index were attained. The correlations between them were analyzed using Pearson's correlation and Student's t-test. Results : The average consumption of alcohol in these subjects was 2.5-fold over social drinkers. The incidence of alcoholic hepatitis was around 30%, while fatty liver 73%, and abnormal GGT 77%, respectively. No specific correlation between average volume of daily alcoholic consumption and alcohol-related hepatic parameters was shown in this study, but correlative tendency between fatty liver and body mass index was exhibited. Conclusions : This study may indicate that alcoholic liver injuries are caused by not just volume of alcohol consumed but more mixed factors including inherited genetic components, body fat mass, foods and other physical or emotional stress.

• 대한핵의학회:학술대회논문집
• /
• 대한핵의학회 1971년도 제10차 학술대회
• /
• pp.81.1-81.1
• /
• 1971

• 정보처리학회논문지B
• /
• 제19B권2호
• /
• pp.123-126
• /
• 2012

본 논문은 생체간이식 전에 복부 MDCT(Multi-Detector Computed Tomography) 영상에서 간 이식편의 체적을 간단하고 정확하게 계산하기 위하여 좌간과 우간을 나누는 방법을 제안하였다. 본 알고리즘은 기증자와 수혜자의 안전을 보장하기 위하여 시스템과 의료진의 상호작업을 최소화 하여 의료진이 수술 전 이식편의 판단을 정확하게 처리할 수 있도록 하였다. 간이 추출된 영상에 좌간과 우간을 나눌 수 있는 2점(중간 정맥(MHV: Middle Hepatic Vein) 내부의 한 점과 좌우문맥(PV: Portal Vein) 분지부에서 한 점)을 선택한다. 선택된 중간정맥 내부의 점을 이용하여 중간정맥을 자동 인식한 후 중간정맥을 기준으로 절개선을 결정하여 문맥 분지부의 한 점을 연결하는 절개면을 형성한다. 좌간과 우간의 체적과 간 전체에 대한 좌우간의 비율을 계산한다. 계산된 체적의 정확성을 입증하기 위해 진단 방사선과 의사가 수동으로 처리하여 계산한 체적과 함께 수술 중 획득한 실측무게와 비교하였다. 실측무게와 수동으로 예측된 체적 사이의 오차에 대한 평균${\pm}$표준편차는 $162.38cm^3{\pm}124.39$이고, 실측무게와 2점을 이용하여 예측된 체적과의 오차에 대한 평균${\pm}$표준편차는 $107.69cm^3{\pm}97.24$이다. 실측무게와 수동으로 예측된 체적의 상관관계는 0.79이고, 실측무게와 2점을 이용하여 예측된 체적의 상관관계는 0.87이다. 그리고 2점을 선택한 후 좌우간을 분할하여 체적을 계산하는 시간을 측정하여 수술실에서 실시간으로 처리 가능한지의 여부를 확인하였다. 한 데이터세트($149.17pages{\pm}55.92$) 당 처리 시간의 평균${\pm}$표준편차는 $57.28sec{\pm}32.81$이다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2009년도 추계학술발표대회
• /
• pp.345-346
• /
• 2009

The segmentation of vessel including portal vein, hepatic vein and artery, from Computed Tomography (CT) images plays an important role in the therapeutic strategies for hepatic diseases. Representing segmented vessels in three dimensional spaces is extremely useful for doctors to plan liver surgery. In this paper, proposed method is focused on smoothing technique of segmented 3D liver vessels, which derived from 3D region growing approach. A pixel expand algorithm has been developed first to avoid vessel lose and disconnection cased by the next smoothing technique. And then a binary volume filtering technique has been implemented and applied to make the segmented binary vessel volume qualitatively smoother. This strategy uses an iterative relaxation process to extract isosurfaces from binary volumes while retaining anatomical structure and important features in the volume. Hard and irregular place in volume image has been eliminated as shown in the result part, which also demonstrated that proposed method is a suitable smoothing solution for post processing of fine vessel segmentation.

• 한국멀티미디어학회논문지
• /
• 제25권5호
• /
• pp.757-768
• /
• 2022

In this paper, we proposed a system that visualizes a hologram device in 3D by utilizing the CT image segmentation function based on artificial intelligence deep learning. The input axial CT medical image is converted into Sagittal and Coronal, and the input image and the converted image are divided into 3D volumes using ResUNet, a deep learning model. In addition, the volume is created by segmenting the tumor region in the segmented liver image. Each result is integrated into one 3D volume, displayed in a medical image viewer, and converted into a video. When the converted video is transmitted to the hologram device and output from the device, a 3D image with a sense of space can be checked. As for the performance of the deep learning model, in Axial, the basic input image, DSC showed 95.0% performance in liver region segmentation and 67.5% in liver tumor region segmentation. If the system is applied to a real-world care environment, additional physical contact is not required, making it safer for patients to explain changes before and after surgery more easily. In addition, it will provide medical staff with information on liver and liver tumors necessary for treatment or surgery in a three-dimensional manner, and help patients manage them after surgery by comparing and observing the liver before and after liver resection.

• Pediatric Gastroenterology, Hepatology & Nutrition
• /
• 제25권6호
• /
• pp.481-488
• /
• 2022

Purpose: Liver transplantation (LT) is the only curative treatment for acute liver failure (ALF) and acute-on-chronic liver failure (ACLF). In high-volume therapeutic plasma exchange (HV-TPE), extracorporeal liver support filters accumulate toxins and improve the coagulation factor by replacing them. In this study, we aimed to evaluate the effectiveness of HV-TPE in pediatric patients with ALF and ACLF. Methods: We reviewed the records of children waiting for LT at Severance Hospital who underwent HV-TPE between 2017 and 2021. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), total and direct bilirubin (TB and DB), gamma-glutamyl transferase (GGT), ammonia, and coagulation parameter-international normalized ratio (INR) were all measured before and after HV-TPE to analyze the liver function. The statistical analysis was performed using IBM SPSS Statistics for Windows, version 26.0 (IBM Co., Armonk, NY, USA). Results: Nine patients underwent HV-TPE with standard medical therapy while waiting for LT. One had neonatal hemochromatosis, four had biliary atresia, and the other four had ALF of unknown etiology. Significant decreases in AST, ALT, TB, DB, GGT, and INR were noted after performing HV-TPE (930.38-331.75 IU/L, 282.62-63.00 IU/L, 11.75-5.59 mg/dL, 8.10-3.66 mg/dL, 205.62-51.75 IU/L, and 3.57-1.50, respectively, p<0.05). All patients underwent LT, and two expired due to acute complications. Conclusion: HV-TPE could remove accumulated toxins and improve coagulation. Therefore, we conclude that HV-TPE can be regarded as a representative bridging therapy before LT.