Gd-EOB-DTPA-enhanced 3.0-Tesla MRI Findings for the Preoperative Detection of Focal Liver Lesions: Comparison with Iodine-enhanced Multi-detector Computed Tomography

박형후,구은회,임인철,이재승,김문집,곽병준,정운관,동경래 한국물리학회 2012 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.61 No.11

The safety of Gd-EOB-DTPA has been confirmed but more study is needed to assess the diagnostic accuracy of Gd-EOB-DTPA-enhanced MRI in patients with hepatocellular carcinoma (HCC) for whom surgical treatment is considered, or for those with a metastatic hepatoma. Research is also needed to examine the rate of detection of hepatic lesions compared to multi-detector computed tomography (MDCT), which is used most frequently to localize and characterize HCC. Gd-EOB-DTPA enhanced magnetic resonance imaging (MRI) and iodine enhanced MDCT imaging were compared for the preoperative detection of focal liver lesions. The clinical usefulness of each method was examined. The current study enrolled 79 patients with focal liver lesions who preoperatively underwent MRI and MDCT. In these patients, there was a less than one month gap between the two diagnostic modalities. Imaging data was taken before and after contrast enhancement in both methods. To evaluate the images, this study analyzed the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in the lesions and liver parenchyma. To compare the sensitivity of the two methods, quantitative analysis of the percentage signal intensity of the liver (PSIL) was performed on a high resolution PACS monitor (paired-samples t-test, p < 0.05). The enhancement was evaluated in consensus by four observers. The enhancement pattern and morphological features during the arterial and delayed phases were correlated between the Gd-EOB-DTPA enhanced MRI findings and iodine enhanced MDCT using an adjusted x2 test. The SNRs, CNRs and PSIL all had a greater detection rate in Gd-EOB-DTPA enhanced MRI than in iodine enhanced MDCT. Hepatocyte-selective uptake was observed 20 minutes after the injection in the focal nodular hyperplasia (FNH, 9/9), adenoma (9/10) and highly differentiated HCC (grade G1, 27/30). Rim enhancement was detected in all metastases (30/30). During the arterial and delayed phases, there was a good overall agreement rate between the gadoxetic acid-enhanced MR and CT (x² test, p < 0.05). For the preoperative detection of focal liver lesions, Gd-EOB-DTPA-enhanced MRI had a higher diagnostic value and higher detection rate than iodine-enhanced MDCT. The arterial and delayed dynamic enhancement patterns, and gadoxetic acid-enhanced MR imaging can provide information on the possible degree of cellular differentiation of HCC, adenoma and metastatic tumors.

전산화단층촬영 영상을 이용한 뇌출혈 질감특징분석

박형후,박지군,최일홍,강상식,노시철,정봉재 한국방사선학회 2015 한국방사선학회 논문지 Vol.9 No.6

본 연구에서 제안된 질감특징분석 알고리즘은 뇌출혈환자의 CT영상을 이용하여 정상영상과 질환영상으로 구분하여, 고유영상 및 실험영상을 생성하고 제안된 컴퓨터보조진단 시스템에 적용하여 6개의 파라메타로 정량적 분석을 통해 뇌출혈 CT영상의 인식률을 도출하고 평가하였다. 결과로 뇌출혈 CT영상 40증례 중에서 각각의 질감 특징값에 대한 인식률은 평균밝기의 경우 100%, 평균대조도의 경우 100%, 평탄도의 경우 100%, 왜곡도의 경우 100%로 높게 나타났고, 균일도의 경우 95%, 엔트로피의 경우 87.5%로 다소 낮은 질환 인식률을 보였다. 따라서 본 연구의 결과를 바탕으로 의료영상의 컴퓨터보조진단 시스템으로 발전된 프로그램을 구현한다면 뇌출혈 CT영상의 질환부위 자동검출 및 정량적 진단이 가능해 컴퓨터보조진단 자료로서 활용이 가능할 것으로 판단되며 최종판독에서 정확성과 판독시간 단축에 유용하게 사용 될 것으로 사료된다. In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

디지털 흉부영상에서 주성분분석을 이용한 폐암인식

박형후,옥치상,강세식,고성진,최석윤,Park, Hyung-Hu,Ok, Chi-Sang,Kang, Se-Sik,Ko, Sung-Jin,Choi, Seok-Yoon 한국정보통신학회 2011 한국정보통신학회논문지 Vol.15 No.7

흉부의 폐질환으로 폐암발생은 꾸준히 증가하고 있다. 일차적인 폐암진단 방법에는 흉부X선영상이다. 흉부X선영상 이용하여 폐암진단을 하기 위해서는 임상경험이 풍부한 의사가 필요하다. 그러나 풍부한 경험을 가진 의사라도 오진이 발생할 수 있고 이한 폐암의 조기진단과 생존률을 낮게 한다. 본 논문에서는 주성분분석을 이용하여 학습영상의 데이터베이스와 질병이 있는 흉부영상을 진단함으로써 컴퓨터보조진단의 기반을 마련하고자 한다. 이를 의사가 진단하기 전의 예비판독의 단계로 이용한다면 오진으로 인한 환자의 조기 진단률의 감소를 줄일 수가 있다. 실험은 정상흉부X선영상과 악성폐암인 기관지암(Bronchogenic Carcinoma)과 양성종양인 육아종(Granuloma)으로 실험하였다. 영상은 주성분분석 후 정상영상과 질환 영상의 고유영상을 추출하고 상호 비교한 뒤 인식효율을 비교하였다. 결과로는 정상영상과 질환영상간의 인식률은 높았으나 질환간의 인식효율은 정상에 비해 다소 떨어지는 것으로 나타났다. 흉부질환간의 인식효율을 높이기 위해서 관련 알고리즘에 관한 연구가 계속 이어진다면 컴퓨터보조진단에 좋은 연구기반이 되리라 생각한다. Risk of lung cancer among lung-related diseases has gradually increased during last decades. The chest digital radiography is the primary diagnosis method for lung cancer. Diagnosing lung cancer using this method requires doctors of ripe experience. Despite their experience there are often wrong diagnoses, which decrease early diagnosis and survival rates of patients. The aim of this study was intended to establish the base on the Computer Aided Diagnosis (CAD) by analyzing Image Recognition Algorithm using Principle component Analysis (PCA) and diagnosing patient's chest X-ray image. The database obtained through this approach enables a doctor to significantly reduce misdiagnosis during the early diagnosis stage, if he or she utilizes it as the preliminary reading step. Case studies were carried out using normal organ, and organs suffering from bronchogenic carcinoma and granuloma. A normal image and unique disease images were extracted after PCA analysis, and their cross-recognition efficiency were compared each other. The result revealed that the recognition rate was much high between normal and disease images, but relatively low between two disease images. In order to increase the recognition efficiency among chest diseases the related algorithms have to be developed continuously in the future study, and such effort will establish the resolute base for CAD.

Fatty Liver 환자의 컴퓨터단층촬영 영상을 이용한 질감특징분석

박형후,박지군,최일홍,강상식,노시철,정봉재 한국방사선학회 2016 한국방사선학회 논문지 Vol.10 No.2

본 실험에서 제안된 질감특징분석 알고리즘은 지방간 환자의 CT영상을 이용하여 정상영상과 질환영상 으로 구분하여, 정상 간 CT영상과 지방간 CT영상을 생성하고 제안된 질감특징분석을 이용한 컴퓨터보조 진단 시스템에 적용하여 6개의 파라메타로 정량적 분석을 통해 지방간 CT영상의 질환 인식률을 도출하고 평가하였다. 결과로 지방간 CT영상 30증례 중에서 각각의 파라메타별 질감특징 값에 대한 인식률은 평균 밝기의 경우 100%, 엔트로피의 경우 96.67%, 왜곡도의 경우 93.33%로 높게 나타났고, 평탄도의 경우 83.3 3%, 균일도의 경우 86.67%, 평균대조도의 경우 80%로 다소 낮은 질환 인식률을 보였다. 따라서 본 연구의 결과를 바탕으로 의료영상의 컴퓨터보조진단 시스템으로 발전된 프로그램을 구현한다면 지방간 CT영상의 질환부위 자동검출 및 정량적 진단이 가능해 컴퓨터보조진단 자료로서 활용이 가능할 것으로 판단되며 최 종판독에서 객관성, 정확성, 판독시간 단축에 유용하게 사용 될 것으로 사료된다. In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some fatty liver patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of fatty liver. As the results of examining over 30 example CT images of fatty liver, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including Average Gray Level, Entropy 96.67%, Skewness 93.33%, and Smoothness while others showed a little low disease recognition rate: 83.33% for Uniformity 86.67% and for Average Contrast 80%. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of fatty liver and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading. Keywords: Fatty Liver, Texture Feature Analysis

골다공증 환자의 Digital 방사선 요추 Image를 이용한 영상분석

박형후(Hyong-Hu Park),이진수(Jin-Soo Lee) 한국콘텐츠학회 2014 한국콘텐츠학회논문지 Vol.14 No.11

본 연구는 골다공증 환자의 Digital 요추 측부 영상을 이용하여 질감특징의 통계적 분석으로 컴퓨터 보조진단 시스템 구현과 질병의 조기진단 및 치료를 위한 실험적인 모형 연구로 신뢰성 있는 보조적 진단 정보를 제공함으로써 골다공증에 대한 정확한 진단 방향을 제시하고자 하였다. 이를 위해서 정상인의 Digital 방사선 요추 측부 영상과 골다공증 환자의 Digital 방사선 요추 측부 영상을 실험 영상으로 하여 설정된 ROI에 대한 통계적 질감특징 값을 6가지 parameter로 나타냈다. 골다공증에 대한 질감특징분석 값 중 Average Gray Level에서 95%로 최고 높은 인식률을 나타내었고, Uniformity에서 80%로 가장 낮은 인식률을 나타내었다. 또한 Average Contrast에서 82.5%, Smoothness에서 90%, Skewness에서 87.5%, Entropy에서 87.5%를 나타내어 6가지 Parameter에서 모두 80%이상의 높은 인식률을 나타내 알고리즘의 안정성을 입증하였다. 따라서 본 연구 결과를 토대로 의료영상의 컴퓨터자동진단 시스템으로 발전된 프로그램을 coding 한다면 의료영상의 병소부위 자동검출, 질병 진단을 위한 예비 진단자료, 질병의 확진을 위한 자료제공, 제한된 장비로도 진단 가능, 의료영상의 판독시간 단축에 유용하게 사용될 수 있으리라 사료된다. This study aimed to propose an accurate diagnostic method for osteoporosis by realizing a computer-aided diagnosis system with the application of the statistical analysis of texture features using digital images of lateral lumbar spine of patients with osteoporosis and providing reliable supplementary diagnostic information by model experimental research for early diagnosis of diseases. For these purposes, digital images of lateral lumbar spine of normal individuals and patients with osteoporosis were used in the experiments, and the values of statistical texture features on the set ROI were expressed in six parameters. Among the texture feature values of the six parameters of osteoporosis, the highest and lowest recognition rates of 95 and 80% were shown in average gray level and uniformity, respectively. Moreover, all the six parameters showed recognition rates of over 80% for osteoporosis: 82.5% in average contrast, 90% in smoothness, 87.5% in skewness, and 87.5% in entropy. Therefore, if a program developing into a computer-aided diagnosis system for medical images is coded based on the results of this study, it is considered possible to be applied to preliminary diagnostic data for automatic detection of lesions and disease diagnosis using medical images, to provide information for definite diagnosis of diseases, to diagnose by limited device, and to be used to shorten the time to analyze medical images.

Texture Feature analysis using Computed Tomography Imaging in Fatty Liver Disease Patients

박형후(Hyong-Hu Park),박지군(Ji-Koon Park),최일홍(Il-Hong Choi),강상식(Sang-Sik Kang),노시철(Si-Cheol Noh),정봉재(Bong-Jae Jung) 한국방사선학회 2016 한국방사선학회 논문지 Vol.10 No.2

본 실험에서 제안된 질감특징분석 알고리즘은 지방간 환자의 CT영상을 이용하여 정상영상과 질환영상으로 구분하여, 정상 간 CT영상과 지방간 CT영상을 생성하고 제안된 질감특징분석을 이용한 컴퓨터보조진단 시스템에 적용하여 6개의 파라메타로 정량적 분석을 통해 지방간 CT영상의 질환 인식률을 도출하고 평가하였다. 결과로 지방간 CT영상 30증례 중에서 각각의 파라메타별 질감특징 값에 대한 인식률은 평균밝기의 경우 100%, 엔트로피의 경우 96.67%, 왜곡도의 경우 93.33%로 높게 나타났고, 평탄도의 경우 83.33%, 균일도의 경우 86.67%, 평균대조도의 경우 80%로 다소 낮은 질환 인식률을 보였다. 따라서 본 연구의 결과를 바탕으로 의료영상의 컴퓨터보조진단 시스템으로 발전된 프로그램을 구현한다면 지방간 CT영상의 질환부위 자동검출 및 정량적 진단이 가능해 컴퓨터보조진단 자료로서 활용이 가능할 것으로 판단되며 최종판독에서 객관성, 정확성, 판독시간 단축에 유용하게 사용 될 것으로 사료된다. In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some fatty liver patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of fatty liver. As the results of examining over 30 example CT images of fatty liver, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including Average Gray Level, Entropy 96.67%, Skewness 93.33%, and Smoothness while others showed a little low disease recognition rate: 83.33% for Uniformity 86.67% and for Average Contrast 80%. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of fatty liver and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

혼합현실 기반 방사선 안전교육 시뮬레이터 플랫폼 개발: 의료분야 중심으로

박형후(Park Hyong-Hu),심재구(Shim Jae-Goo),권순무(Kwon Soon-Mu) 대한방사선과학회(구 대한방사선기술학회) 2021 방사선기술과학 Vol.44 No.2

In this study, safety education contents for medical radiation workers were produced based on Mixed Reality(MR). Currently, safety training for radiation workers is based on theory. This is insufficient in terms of worker satisfaction and efficiency. To address this, we created ICT(Information and Communication Technologies)-based MR radiation worker safety education content. The expected effect of Mixed Reality worker safety education content is that education is possible without space and time constraints, realistic education is possible without on-site training, and interaction between images is possible through reality-based 3D images, enabling self-directed learning Is that. In addition, learning in a virtual space expressed through HMD(Head Mounted Display) is expected to make education more enjoyable and increase concentration, thereby increasing the efficiency of education. A quantitative evaluation was conducted by an accredited institution and a qualitative evaluation was performed on users, which received excellent evaluation. The MR safety education conducted in this study is expected to be of great help to the education of medical radiation workers, and is expected to develop into a new educational paradigm as online education in accordance with Corona 19 progresses.

신부전환자의 신장이식 전후 골밀도변화 분석

박형후(Hyong-Hu Park),옥치상(Chi-Sang Ok),박영인(Young-In Park),이진수(Jin-Soo Lee),김창수(Changsoo Kim) 한국콘텐츠학회 2012 한국콘텐츠학회논문지 Vol.12 No.9

골밀도 감소에 의해서 발생되는 골감소증, 골다공증 등은 폐경 후 여성에게 유병률이 높은 질환이며, 골다공증 골절에 따른 사회적 의료비 상승으로 의학적 관심이 급증하고 있다. 신부전환자는 체내에 비타민D 합성 능력이 저하되어 칼슘 흡수가 감소하여 뼈의 섬유화가 발생되고, 골밀도가 감소하는 현상이 나타난다. 따라서 신부전환자는 신장 기능 장애로 그치지 않고, 골다공증과 같은 골밀도 감소에 따른 합병증에 노출되어 있다. 본 연구에서는 치료 중에 있는 신부전환자들의 골밀도 변화를 관찰하였고, 신장이식 전후에서 발견되는 골밀도 변화를 분석하였다. 조사대상은 부산 B종합병원 신장내과 내원환자 중 신부전환자 214명을 신장이식의 유무에 따라 골밀도의 변화를 세대별, 성별로 나누어 분석했다. 분석결과 신장이식 환자군에서는 골밀도가 유지되거나 개선되었지만, 비신장이식 환자군에서는 골밀도가 꾸준히 나빠지는 결과를 보였다. 신부전환자는 신장이식을 받는 것이 최선의 치료책으로 사료되며, 신장이식을 통해서 골밀도의 개선이 가능함을 확인하였다. 이는 추가적으로 예상되는 합병증을 예방하기 위한 자료로도 활용할 수 있다. Disease, such as osteopenia, osteoporosis, etc caused by reduced bone density are common to women after menopause and as the social medical cost increases due to osteoporosis fractures the medical interest in bone density reduction has increased. The bone density reduction is observed even for renal failure patients, due to their decreased ability to synthesize vitamin D which leads to bone fibrosis because of deficiency in calcium absorption. Thus renal failure patients not only suffer from kidney dysfunction, but also are exposed to complications, such as osteoporosis, due to reduced bone density. This research observed the change in bone density of patients receiving renal failure treatment and analyzed the change in bone density before and after kidney transplantations. Subjects were 214 renal failure patients at the department of nephrology Busan B General Hospital. The change in bone density was studied for subjects with and without kidney transplantation according to their age and sex. The research showed improvement or maintenance of bone density for subjects that received kidney transplantation, but showed a tendency of consistent decrease in bone density for subjects without kidney transplantation. Kidney transplantation can be considered as the best cure for renal failure patients, and this researched confirmed that bone density can be improved through kidney transplantation. Thus, this study can also be used as data for preventing complications due to renal failures.

뇌경색 감별진단을 위한 컴퓨터보조진단 응용: Brain CT Images 적용

박형후(Hyong-Hu Park),조문주(Mun-Joo Cho),임인철(In-Chul Im),이진수(Jin-Soo Lee) 한국방사선학회 2016 한국방사선학회 논문지 Vol.10 No.8

본 연구는 통계적 속성에 기반한 질감특징값 분석을 바탕으로 뇌 전산화단층촬영 영상에서 정상과 뇌경 색의 컴퓨터보조진단의 적용 가능성을 알아보고자 하였다. 실험은 질감특징값을 나타내는 6개의 파라미터 를 이용한 질환인식률 평가와 ROC curve를 분석하였다. 그 결과 평균밝기 88%, 대조도 92%, 평탄도 94%, 균일도 88%, 엔트로피 84%의 높은 질환인식률을 나타내었다. 하지만 왜곡도의 경우 58%로 다소 낮은 질 환 인식률을 나타내었다. ROC curve를 이용한 분석에서 각 파라미터의 곡선아래면적이 0.886(p=0.0001)이 상을 나타내어 질환인식에 의미가 있는 결과로 나타났다. 또한 각 파라미터의 cut-off값 결정으로 컴퓨터보 조진단을 통한 질환예측이 가능할 것으로 판단된다. In this study, based on the analysis of texture feature values of statistical properties. And we examined the normal and the applicability of the computer-aided diagnosis of cerebral infarction in the brain computed tomography images. The experiment was analyzed to evaluate the ROC curve recognition rate of disease using six parameters representing the feature values of the texture. As a result, it showed average mean 88%, variance 92%, relative smoothness 94%, uniformity of 88%, a high disease recognition rate of entropy 84%. However, it showed a slightly lower disease recognition rate and 58% for skewness. In the analysis using ROC curve, the area under the curve for each parameter indicates 0.886 (p = 0.0001) or more, resulted in a meaningful recognition of the disease. Further, to determine the cut-off values for each parameter are determined to be the prediction of disease through the computer-aided diagnosis.

핀홀카메라를 이용한 X선 포톤 플루엔스 측정

박형후(Hyong-Hu Park),강상식(Sang-sik Kang),정봉재(Bong-Jae Jung),노시철(Si-Cheol Noh),박지군(Ji-Koon Park) 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.6